WorldWideScience

Sample records for relation semantics extracted

  1. Enhancing biomedical text summarization using semantic relation extraction.

    Directory of Open Access Journals (Sweden)

    Yue Shang

    Full Text Available Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1 We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2 We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3 For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

  2. Enhancing biomedical text summarization using semantic relation extraction.

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    Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

    2011-01-01

    Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

  3. Exploring DBpedia and Wikipedia for Portuguese Semantic Relationship Extraction

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    David Soares Batista

    2013-07-01

    Full Text Available The identification of semantic relationships, as expressed between named entities in text, is an important step for extracting knowledge from large document collections, such as the Web. Previous works have addressed this task for the English language through supervised learning techniques for automatic classification. The current state of the art involves the use of learning methods based on string kernels. However, such approaches require manually annotated training data for each type of semantic relationship, and have scalability problems when tens or hundreds of different types of relationships have to be extracted. This article discusses an approach for distantly supervised relation extraction over texts written in the Portuguese language, which uses an efficient technique for measuring similarity between relation instances, based on minwise hashing and on locality sensitive hashing. In the proposed method, the training examples are automatically collected from Wikipedia, corresponding to sentences that express semantic relationships between pairs of entities extracted from DBPedia. These examples are represented as sets of character quadgrams and other representative elements. The sets are indexed in a data structure that implements the idea of locality-sensitive hashing. To check which semantic relationship is expressed between a given pair of entities referenced in a sentence, the most similar training examples are searched, based on an approximation to the Jaccard coefficient, obtained through min-hashing. The relation class is assigned with basis on the weighted votes of the most similar examples. Tests with a dataset from Wikipedia validate the suitability of the proposed method, showing, for instance, that the method is able to extract 10 different types of semantic relations, 8 of them corresponding to asymmetric relations, with an average score of 55.6%, measured in terms of F1.

  4. Semantic Location Extraction from Crowdsourced Data

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    Koswatte, S.; Mcdougall, K.; Liu, X.

    2016-06-01

    Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction.

  5. SEMANTIC LOCATION EXTRACTION FROM CROWDSOURCED DATA

    Directory of Open Access Journals (Sweden)

    S. Koswatte

    2016-06-01

    Full Text Available Crowdsourced Data (CSD has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network. This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction.

  6. Extracting Semantic Information from Visual Data: A Survey

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    Qiang Liu

    2016-03-01

    Full Text Available The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.

  7. Semi-Supervised Learning to Identify UMLS Semantic Relations.

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    Luo, Yuan; Uzuner, Ozlem

    2014-01-01

    The UMLS Semantic Network is constructed by experts and requires periodic expert review to update. We propose and implement a semi-supervised approach for automatically identifying UMLS semantic relations from narrative text in PubMed. Our method analyzes biomedical narrative text to collect semantic entity pairs, and extracts multiple semantic, syntactic and orthographic features for the collected pairs. We experiment with seeded k-means clustering with various distance metrics. We create and annotate a ground truth corpus according to the top two levels of the UMLS semantic relation hierarchy. We evaluate our system on this corpus and characterize the learning curves of different clustering configuration. Using KL divergence consistently performs the best on the held-out test data. With full seeding, we obtain macro-averaged F-measures above 70% for clustering the top level UMLS relations (2-way), and above 50% for clustering the second level relations (7-way).

  8. Semantic Information Extraction of Lanes Based on Onboard Camera Videos

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    Tang, L.; Deng, T.; Ren, C.

    2018-04-01

    In the field of autonomous driving, semantic information of lanes is very important. This paper proposes a method of automatic detection of lanes and extraction of semantic information from onboard camera videos. The proposed method firstly detects the edges of lanes by the grayscale gradient direction, and improves the Probabilistic Hough transform to fit them; then, it uses the vanishing point principle to calculate the lane geometrical position, and uses lane characteristics to extract lane semantic information by the classification of decision trees. In the experiment, 216 road video images captured by a camera mounted onboard a moving vehicle were used to detect lanes and extract lane semantic information. The results show that the proposed method can accurately identify lane semantics from video images.

  9. The methodology of semantic analysis for extracting physical effects

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    Fomenkova, M. A.; Kamaev, V. A.; Korobkin, D. M.; Fomenkov, S. A.

    2017-01-01

    The paper represents new methodology of semantic analysis for physical effects extracting. This methodology is based on the Tuzov ontology that formally describes the Russian language. In this paper, semantic patterns were described to extract structural physical information in the form of physical effects. A new algorithm of text analysis was described.

  10. Domain XML semantic integration based on extraction rules and ontology mapping

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    Huayu LI

    2016-08-01

    Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

  11. ZK DrugResist 2.0: A TextMiner to extract semantic relations of drug resistance from PubMed.

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    Khalid, Zoya; Sezerman, Osman Ugur

    2017-05-01

    Extracting useful knowledge from an unstructured textual data is a challenging task for biologists, since biomedical literature is growing exponentially on a daily basis. Building an automated method for such tasks is gaining much attention of researchers. ZK DrugResist is an online tool that automatically extracts mutations and expression changes associated with drug resistance from PubMed. In this study we have extended our tool to include semantic relations extracted from biomedical text covering drug resistance and established a server including both of these features. Our system was tested for three relations, Resistance (R), Intermediate (I) and Susceptible (S) by applying hybrid feature set. From the last few decades the focus has changed to hybrid approaches as it provides better results. In our case this approach combines rule-based methods with machine learning techniques. The results showed 97.67% accuracy with 96% precision, recall and F-measure. The results have outperformed the previously existing relation extraction systems thus can facilitate computational analysis of drug resistance against complex diseases and further can be implemented on other areas of biomedicine. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

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    Rong Gui

    2016-08-01

    Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

  13. Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction

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    Andrea Cavallaro

    2004-06-01

    Full Text Available The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an automatic manner. These two subproblems are not mutually independent, and they can benefit from interactions with each other. In this paper, a framework for such interaction is formulated. This representation scheme based on region segmentation and semantic segmentation is compatible with the view that image analysis and scene understanding problems can be decomposed into low-level and high-level tasks. Low-level tasks pertain to region-oriented processing, whereas the high-level tasks are closely related to object-level processing. This approach emulates the human visual system: what one “sees” in a scene depends on the scene itself (region segmentation as well as on the cognitive task (semantic segmentation at hand. The higher-level segmentation results in a partition corresponding to semantic video objects. Semantic video objects do not usually have invariant physical properties and the definition depends on the application. Hence, the definition incorporates complex domain-specific knowledge and is not easy to generalize. For the specific implementation used in this paper, motion is used as a clue to semantic information. In this framework, an automatic algorithm is presented for computing the semantic partition based on color change detection. The change detection strategy is designed to be immune to the sensor noise and local illumination variations. The lower-level segmentation identifies the partition corresponding to perceptually uniform regions. These regions are derived by clustering in an N-dimensional feature space, composed of static as well as dynamic image attributes. We propose an interaction mechanism between the semantic and the region partitions which allows to

  14. Sortal anaphora resolution to enhance relation extraction from biomedical literature.

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    Kilicoglu, Halil; Rosemblat, Graciela; Fiszman, Marcelo; Rindflesch, Thomas C

    2016-04-14

    Entity coreference is common in biomedical literature and it can affect text understanding systems that rely on accurate identification of named entities, such as relation extraction and automatic summarization. Coreference resolution is a foundational yet challenging natural language processing task which, if performed successfully, is likely to enhance such systems significantly. In this paper, we propose a semantically oriented, rule-based method to resolve sortal anaphora, a specific type of coreference that forms the majority of coreference instances in biomedical literature. The method addresses all entity types and relies on linguistic components of SemRep, a broad-coverage biomedical relation extraction system. It has been incorporated into SemRep, extending its core semantic interpretation capability from sentence level to discourse level. We evaluated our sortal anaphora resolution method in several ways. The first evaluation specifically focused on sortal anaphora relations. Our methodology achieved a F1 score of 59.6 on the test portion of a manually annotated corpus of 320 Medline abstracts, a 4-fold improvement over the baseline method. Investigating the impact of sortal anaphora resolution on relation extraction, we found that the overall effect was positive, with 50 % of the changes involving uninformative relations being replaced by more specific and informative ones, while 35 % of the changes had no effect, and only 15 % were negative. We estimate that anaphora resolution results in changes in about 1.5 % of approximately 82 million semantic relations extracted from the entire PubMed. Our results demonstrate that a heavily semantic approach to sortal anaphora resolution is largely effective for biomedical literature. Our evaluation and error analysis highlight some areas for further improvements, such as coordination processing and intra-sentential antecedent selection.

  15. Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation.

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    Huang, Chung-Chi; Lu, Zhiyong

    2016-01-01

    Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order

  16. Semantic feature extraction for interior environment understanding and retrieval

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    Lei, Zhibin; Liang, Yufeng

    1998-12-01

    In this paper, we propose a novel system of semantic feature extraction and retrieval for interior design and decoration application. The system, V2ID(Virtual Visual Interior Design), uses colored texture and spatial edge layout to obtain simple information about global room environment. We address the domain-specific segmentation problem in our application and present techniques for obtaining semantic features from a room environment. We also discuss heuristics for making use of these features (color, texture, edge layout, and shape), to retrieve objects from an existing database. The final resynthesized room environment, with the original scene and objects from the database, is created for the purpose of animation and virtual walk-through.

  17. Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD.

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    Bullinaria, John A; Levy, Joseph P

    2012-09-01

    In a previous article, we presented a systematic computational study of the extraction of semantic representations from the word-word co-occurrence statistics of large text corpora. The conclusion was that semantic vectors of pointwise mutual information values from very small co-occurrence windows, together with a cosine distance measure, consistently resulted in the best representations across a range of psychologically relevant semantic tasks. This article extends that study by investigating the use of three further factors--namely, the application of stop-lists, word stemming, and dimensionality reduction using singular value decomposition (SVD)--that have been used to provide improved performance elsewhere. It also introduces an additional semantic task and explores the advantages of using a much larger corpus. This leads to the discovery and analysis of improved SVD-based methods for generating semantic representations (that provide new state-of-the-art performance on a standard TOEFL task) and the identification and discussion of problems and misleading results that can arise without a full systematic study.

  18. SPECTRa-T: machine-based data extraction and semantic searching of chemistry e-theses.

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    Downing, Jim; Harvey, Matt J; Morgan, Peter B; Murray-Rust, Peter; Rzepa, Henry S; Stewart, Diana C; Tonge, Alan P; Townsend, Joe A

    2010-02-22

    The SPECTRa-T project has developed text-mining tools to extract named chemical entities (NCEs), such as chemical names and terms, and chemical objects (COs), e.g., experimental spectral assignments and physical chemistry properties, from electronic theses (e-theses). Although NCEs were readily identified within the two major document formats studied, only the use of structured documents enabled identification of chemical objects and their association with the relevant chemical entity (e.g., systematic chemical name). A corpus of theses was analyzed and it is shown that a high degree of semantic information can be extracted from structured documents. This integrated information has been deposited in a persistent Resource Description Framework (RDF) triple-store that allows users to conduct semantic searches. The strength and weaknesses of several document formats are reviewed.

  19. Modification Semantics in Now-Relative Databases

    DEFF Research Database (Denmark)

    Torp, Kristian; Jensen, Christian Søndergaard; Snodgrass, R. T.

    2004-01-01

    Most real-world databases record time-varying information. In such databases, the notion of ??the current time,?? or NOW, occurs naturally and prominently. For example, when capturing the past states of a relation using begin and end time columns, tuples that are part of the current state have some...... past time as their begin time and NOW as their end time. While the semantics of such variable databases has been described in detail and is well understood, the modification of variable databases remains unexplored. This paper defines the semantics of modifications involving the variable NOW. More...... specifically,  the problems with modifications in the presence of NOW are explored, illustrating that the main problems are with modifications of tuples that reach into the future. The paper defines the semantics of modifications?including insertions, deletions, and updates?of databases without NOW, with NOW...

  20. Intelligence related upper alpha desynchronization in a semantic memory task.

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    Doppelmayr, M; Klimesch, W; Hödlmoser, K; Sauseng, P; Gruber, W

    2005-07-30

    Recent evidence shows that event-related (upper) alpha desynchronization (ERD) is related to cognitive performance. Several studies observed a positive, some a negative relationship. The latter finding, interpreted in terms of the neural efficiency hypothesis, suggests that good performance is associated with a more 'efficient', smaller extent of cortical activation. Other studies found that ERD increases with semantic processing demands and that this increase is larger for good performers. Studies supporting the neural efficiency hypothesis used tasks that do not specifically require semantic processing. Thus, we assume that the lack of semantic processing demands may at least in part be responsible for the reduced ERD. In the present study we measured ERD during a difficult verbal-semantic task. The findings demonstrate that during semantic processing, more intelligent (as compared to less intelligent) subjects exhibited a significantly larger upper alpha ERD over the left hemisphere. We conclude that more intelligent subjects exhibit a more extensive activation in a semantic processing system and suggest that divergent findings regarding the neural efficiency hypotheses are due to task specific differences in semantic processing demands.

  1. A semantic-based method for extracting concept definitions from scientific publications: evaluation in the autism phenotype domain

    OpenAIRE

    Hassanpour, Saeed; O?Connor, Martin J; Das, Amar K

    2013-01-01

    Background A variety of informatics approaches have been developed that use information retrieval, NLP and text-mining techniques to identify biomedical concepts and relations within scientific publications or their sentences. These approaches have not typically addressed the challenge of extracting more complex knowledge such as biomedical definitions. In our efforts to facilitate knowledge acquisition of rule-based definitions of autism phenotypes, we have developed a novel semantic-based t...

  2. Semantator: annotating clinical narratives with semantic web ontologies.

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    Song, Dezhao; Chute, Christopher G; Tao, Cui

    2012-01-01

    To facilitate clinical research, clinical data needs to be stored in a machine processable and understandable way. Manual annotating clinical data is time consuming. Automatic approaches (e.g., Natural Language Processing systems) have been adopted to convert such data into structured formats; however, the quality of such automatically extracted data may not always be satisfying. In this paper, we propose Semantator, a semi-automatic tool for document annotation with Semantic Web ontologies. With a loaded free text document and an ontology, Semantator supports the creation/deletion of ontology instances for any document fragment, linking/disconnecting instances with the properties in the ontology, and also enables automatic annotation by connecting to the NCBO annotator and cTAKES. By representing annotations in Semantic Web standards, Semantator supports reasoning based upon the underlying semantics of the owl:disjointWith and owl:equivalentClass predicates. We present discussions based on user experiences of using Semantator.

  3. Spatial Relation Predicates in Topographic Feature Semantics

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    Varanka, Dalia E.; Caro, Holly K.

    2013-01-01

    Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

  4. Semantic relations differentially impact associative recognition memory: electrophysiological evidence.

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    Kriukova, Olga; Bridger, Emma; Mecklinger, Axel

    2013-10-01

    Though associative recognition memory is thought to rely primarily on recollection, recent research indicates that familiarity might also make a substantial contribution when to-be-learned items are integrated into a coherent structure by means of an existing semantic relation. It remains unclear how different types of semantic relations, such as categorical (e.g., dancer-singer) and thematic (e.g., dancer-stage) relations might affect associative recognition, however. Using event-related potentials (ERPs), we addressed this question by manipulating the type of semantic link between paired words in an associative recognition memory experiment. An early midfrontal old/new effect, typically linked to familiarity, was observed across the relation types. In contrast, a robust left parietal old/new effect was found in the categorical condition only, suggesting a clear contribution of recollection to associative recognition for this kind of pairs. One interpretation of this pattern is that familiarity was sufficiently diagnostic for associative recognition of thematic relations, which could result from the integrative nature of the thematic relatedness compared to the similarity-based nature of categorical pairs. The present study suggests that the extent to which recollection and familiarity are involved in associative recognition is at least in part determined by the properties of semantic relations between the paired associates. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. ScholarLens: extracting competences from research publications for the automatic generation of semantic user profiles

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    Bahar Sateli

    2017-07-01

    Full Text Available Motivation Scientists increasingly rely on intelligent information systems to help them in their daily tasks, in particular for managing research objects, like publications or datasets. The relatively young research field of Semantic Publishing has been addressing the question how scientific applications can be improved through semantically rich representations of research objects, in order to facilitate their discovery and re-use. To complement the efforts in this area, we propose an automatic workflow to construct semantic user profiles of scholars, so that scholarly applications, like digital libraries or data repositories, can better understand their users’ interests, tasks, and competences, by incorporating these user profiles in their design. To make the user profiles sharable across applications, we propose to build them based on standard semantic web technologies, in particular the Resource Description Framework (RDF for representing user profiles and Linked Open Data (LOD sources for representing competence topics. To avoid the cold start problem, we suggest to automatically populate these profiles by analyzing the publications (co-authored by users, which we hypothesize reflect their research competences. Results We developed a novel approach, ScholarLens, which can automatically generate semantic user profiles for authors of scholarly literature. For modeling the competences of scholarly users and groups, we surveyed a number of existing linked open data vocabularies. In accordance with the LOD best practices, we propose an RDF Schema (RDFS based model for competence records that reuses existing vocabularies where appropriate. To automate the creation of semantic user profiles, we developed a complete, automated workflow that can generate semantic user profiles by analyzing full-text research articles through various natural language processing (NLP techniques. In our method, we start by processing a set of research articles for a

  6. Using Semantic Linking to Understand Persons’ Networks Extracted from Text

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    Alessio Palmero Aprosio

    2017-11-01

    Full Text Available In this work, we describe a methodology to interpret large persons’ networks extracted from text by classifying cliques using the DBpedia ontology. The approach relies on a combination of NLP, Semantic web technologies, and network analysis. The classification methodology that first starts from single nodes and then generalizes to cliques is effective in terms of performance and is able to deal also with nodes that are not linked to Wikipedia. The gold standard manually developed for evaluation shows that groups of co-occurring entities share in most of the cases a category that can be automatically assigned. This holds for both languages considered in this study. The outcome of this work may be of interest to enhance the readability of large networks and to provide an additional semantic layer on top of cliques. This would greatly help humanities scholars when dealing with large amounts of textual data that need to be interpreted or categorized. Furthermore, it represents an unsupervised approach to automatically extend DBpedia starting from a corpus.

  7. Semantic Query Processing : Estimating Relational Purity

    NARCIS (Netherlands)

    Kalo, Jan-Christoph; Lofi, C.; Maseli, René Pascal; Balke, Wolf-Tilo; Leyer, M.

    2017-01-01

    The use of semantic information found in structured knowledge bases has become an integral part of the processing pipeline of modern intelligent in-
    formation systems. However, such semantic information is frequently insuffi-cient to capture the rich semantics demanded by the applications, and

  8. Meaningful Memory in Acute Anorexia Nervosa Patients-Comparing Recall, Learning, and Recognition of Semantically Related and Semantically Unrelated Word Stimuli.

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    Terhoeven, Valentin; Kallen, Ursula; Ingenerf, Katrin; Aschenbrenner, Steffen; Weisbrod, Matthias; Herzog, Wolfgang; Brockmeyer, Timo; Friederich, Hans-Christoph; Nikendei, Christoph

    2017-03-01

    It is unclear whether observed memory impairment in anorexia nervosa (AN) depends on the semantic structure (categorized words) of material to be encoded. We aimed to investigate the processing of semantically related information in AN. Memory performance was assessed in a recall, learning, and recognition test in 27 adult women with AN (19 restricting, 8 binge-eating/purging subtype; average disease duration: 9.32 years) and 30 healthy controls using an extended version of the Rey Auditory Verbal Learning Test, applying semantically related and unrelated word stimuli. Short-term memory (immediate recall, learning), regardless of semantics of the words, was significantly worse in AN patients, whereas long-term memory (delayed recall, recognition) did not differ between AN patients and controls. Semantics of stimuli do not have a better effect on memory recall in AN compared to CO. Impaired short-term versus long-term memory is discussed in relation to dysfunctional working memory in AN. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

  9. Categorizing words through semantic memory navigation

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    Borge-Holthoefer, J.; Arenas, A.

    2010-03-01

    Semantic memory is the cognitive system devoted to storage and retrieval of conceptual knowledge. Empirical data indicate that semantic memory is organized in a network structure. Everyday experience shows that word search and retrieval processes provide fluent and coherent speech, i.e. are efficient. This implies either that semantic memory encodes, besides thousands of words, different kind of links for different relationships (introducing greater complexity and storage costs), or that the structure evolves facilitating the differentiation between long-lasting semantic relations from incidental, phenomenological ones. Assuming the latter possibility, we explore a mechanism to disentangle the underlying semantic backbone which comprises conceptual structure (extraction of categorical relations between pairs of words), from the rest of information present in the structure. To this end, we first present and characterize an empirical data set modeled as a network, then we simulate a stochastic cognitive navigation on this topology. We schematize this latter process as uncorrelated random walks from node to node, which converge to a feature vectors network. By doing so we both introduce a novel mechanism for information retrieval, and point at the problem of category formation in close connection to linguistic and non-linguistic experience.

  10. A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set

    Directory of Open Access Journals (Sweden)

    Abdul Wahab Muzaffar

    2015-01-01

    Full Text Available The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.

  11. Exploiting Semantic Search Methodologies to Analyse Fast Nuclear Reactor Nuclear Related Information

    International Nuclear Information System (INIS)

    Costantini, L.

    2016-01-01

    Full text: This paper describes an experiment to evaluate the outcomes of using the semantic search engine together with the entity extraction approach and the visualisation tools in large set of nuclear data related to fast nuclear reactors (FNR) documents originated from INIS database and the IAEA web publication. The INIS database has been used because is the larger collection of nuclear related data and a sub-set of it can be utilised to verify the efficiency and the effectiveness of this approach. In a nutshell, the goal of the study was to: 1) find and monitor documents dealing with FNR; 2) building knowledge base (KB) according to the FNR nuclear components and populate the KB with relevant documents; 3) communicate the conclusion of the analysis by utilising visualisation tools. The semantic search engine used in the case study has the capability to perform what is called evidential reasoning: accruing, weighing and evaluating the evidence to determinate a mathematical score for each article that measures its relevance to the subject of interest. This approach provides a means to differentiate between articles that closely meet the search criteria versus those less relevant articles. Tovek software platform was chosen for this case study. (author

  12. WEATHER FORECAST DATA SEMANTIC ANALYSIS IN F-LOGIC

    Directory of Open Access Journals (Sweden)

    Ana Meštrović

    2007-06-01

    Full Text Available This paper addresses the semantic analysis problem in a spoken dialog system developed for the domain of weather forecasts. The main goal of semantic analysis is to extract the meaning from the spoken utterances and to transform it into a domain database format. In this work a semantic database for the domain of weather forecasts is represented using the F-logic formalism. Semantic knowledge is captured through semantic categories a semantic dictionary using phrases and output templates. Procedures for semantic analysis of Croatian weather data combine parsing techniques for Croatian language and slot filling approach. Semantic analysis is conducted in three phases. In the first phase the main semantic category for the input utterance is determined. The lattices are used for hierarchical semantic relation representation and main category derivation. In the second phase semantic units are analyzed and knowledge slots in the database are filled. Since some slot values of input data are missing in the third phase, incomplete data is updated with missing values. All rules for semantic analysis are defined in the F-logic and implemented using the FLORA-2 system. The results of semantic analysis evaluation in terms of frame and slot error rates are presented.

  13. Determining Semantically Related Significant Genes.

    Science.gov (United States)

    Taha, Kamal

    2014-01-01

    GO relation embodies some aspects of existence dependency. If GO term xis existence-dependent on GO term y, the presence of y implies the presence of x. Therefore, the genes annotated with the function of the GO term y are usually functionally and semantically related to the genes annotated with the function of the GO term x. A large number of gene set enrichment analysis methods have been developed in recent years for analyzing gene sets enrichment. However, most of these methods overlook the structural dependencies between GO terms in GO graph by not considering the concept of existence dependency. We propose in this paper a biological search engine called RSGSearch that identifies enriched sets of genes annotated with different functions using the concept of existence dependency. We observe that GO term xcannot be existence-dependent on GO term y, if x- and y- have the same specificity (biological characteristics). After encoding into a numeric format the contributions of GO terms annotating target genes to the semantics of their lowest common ancestors (LCAs), RSGSearch uses microarray experiment to identify the most significant LCA that annotates the result genes. We evaluated RSGSearch experimentally and compared it with five gene set enrichment systems. Results showed marked improvement.

  14. Latent semantic analysis.

    Science.gov (United States)

    Evangelopoulos, Nicholas E

    2013-11-01

    This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individual words are represented as vectors. LSA as a computational technique uses linear algebra to extract dimensions that represent that space. This representation enables the computation of similarity among terms and documents, categorization of terms and documents, and summarization of large collections of documents using automated procedures that mimic the way humans perform similar cognitive tasks. We present some technical details, various illustrative examples, and discuss a number of applications from linguistics, psychology, cognitive science, education, information science, and analysis of textual data in general. WIREs Cogn Sci 2013, 4:683-692. doi: 10.1002/wcs.1254 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. © 2013 John Wiley & Sons, Ltd.

  15. Age-related effects on perceptual and semantic encoding in memory.

    Science.gov (United States)

    Kuo, M C C; Liu, K P Y; Ting, K H; Chan, C C H

    2014-03-07

    This study examined the age-related subsequent memory effect (SME) in perceptual and semantic encoding using event-related potentials (ERPs). Seventeen younger adults and 17 older adults studied a series of Chinese characters either perceptually (by inspecting orthographic components) or semantically (by determining whether the depicted object makes sounds). The two tasks had similar levels of difficulty. The participants made studied or unstudied judgments during the recognition phase. Younger adults performed better in both conditions, with significant SMEs detected in the time windows of P2, N3, P550, and late positive component (LPC). In the older group, SMEs were observed in the P2 and N3 latencies in both conditions but were only detected in the P550 in the semantic condition. Between-group analyses showed larger frontal and central SMEs in the younger sample in the LPC latency regardless of encoding type. Aging effect appears to be stronger on influencing perceptual than semantic encoding processes. The effects seem to be associated with a decline in updating and maintaining representations during perceptual encoding. The age-related decline in the encoding function may be due in part to changes in frontal lobe function. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

  16. CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives.

    Science.gov (United States)

    Tao, Cui; Wei, Wei-Qi; Solbrig, Harold R; Savova, Guergana; Chute, Christopher G

    2010-11-13

    Using Semantic-Web specifications to represent temporal information in clinical narratives is an important step for temporal reasoning and answering time-oriented queries. Existing temporal models are either not compatible with the powerful reasoning tools developed for the Semantic Web, or designed only for structured clinical data and therefore are not ready to be applied on natural-language-based clinical narrative reports directly. We have developed a Semantic-Web ontology which is called Clinical Narrative Temporal Relation ontology. Using this ontology, temporal information in clinical narratives can be represented as RDF (Resource Description Framework) triples. More temporal information and relations can then be inferred by Semantic-Web based reasoning tools. Experimental results show that this ontology can represent temporal information in real clinical narratives successfully.

  17. A semantic-based method for extracting concept definitions from scientific publications: evaluation in the autism phenotype domain.

    Science.gov (United States)

    Hassanpour, Saeed; O'Connor, Martin J; Das, Amar K

    2013-08-12

    A variety of informatics approaches have been developed that use information retrieval, NLP and text-mining techniques to identify biomedical concepts and relations within scientific publications or their sentences. These approaches have not typically addressed the challenge of extracting more complex knowledge such as biomedical definitions. In our efforts to facilitate knowledge acquisition of rule-based definitions of autism phenotypes, we have developed a novel semantic-based text-mining approach that can automatically identify such definitions within text. Using an existing knowledge base of 156 autism phenotype definitions and an annotated corpus of 26 source articles containing such definitions, we evaluated and compared the average rank of correctly identified rule definition or corresponding rule template using both our semantic-based approach and a standard term-based approach. We examined three separate scenarios: (1) the snippet of text contained a definition already in the knowledge base; (2) the snippet contained an alternative definition for a concept in the knowledge base; and (3) the snippet contained a definition not in the knowledge base. Our semantic-based approach had a higher average rank than the term-based approach for each of the three scenarios (scenario 1: 3.8 vs. 5.0; scenario 2: 2.8 vs. 4.9; and scenario 3: 4.5 vs. 6.2), with each comparison significant at the p-value of 0.05 using the Wilcoxon signed-rank test. Our work shows that leveraging existing domain knowledge in the information extraction of biomedical definitions significantly improves the correct identification of such knowledge within sentences. Our method can thus help researchers rapidly acquire knowledge about biomedical definitions that are specified and evolving within an ever-growing corpus of scientific publications.

  18. A Cross-Cultural Examination of Semantic Relations.

    Science.gov (United States)

    Raybeck, Douglas; Herrmann, Douglas

    1990-01-01

    Reports on a cross-cultural investigation of semantic relations, including antonyms, synonyms, and class inclusion, among bilingual adult subjects in the United States, England, Italy, Greece, Yugoslavia, Pakistan, and Hong Kong. Found significant agreement across cultures, especially for antinomy. Results in general support theories of linguistic…

  19. Semantic relations and compound transparency: A regression study in CARIN theory

    Directory of Open Access Journals (Sweden)

    Pham Hien

    2013-01-01

    Full Text Available According to the CARIN theory of Gagné and Shoben (1997, conceptual relations play an important role in compound interpretation. This study develops three measures gauging the role of conceptual relations, and pits these measures against measures based on latent semantic analysis (Landauer & Dumais, 1997. The CARIN measures successfully predict response latencies in a familiarity categorization task, in a semantic transparency task, and in visual lexical decision. Of the measures based on latent semantic analysis, only a measure orthogonal to the conceptual relations, which instead gauges the extent to which the concepts for the compound’s head and the compound itself are discriminated, also reached significance. Results further indicate that in tasks requiring careful assessment of the meaning of the compound, general knowledge of conceptual relations plays a central role, whereas in the lexical decision task, attention shifts to co-activated meanings and the specifics of the conceptual relations realized in the compound’s modifier family.

  20. Principal semantic components of language and the measurement of meaning.

    Science.gov (United States)

    Samsonovich, Alexei V; Samsonovic, Alexei V; Ascoli, Giorgio A

    2010-06-11

    Metric systems for semantics, or semantic cognitive maps, are allocations of words or other representations in a metric space based on their meaning. Existing methods for semantic mapping, such as Latent Semantic Analysis and Latent Dirichlet Allocation, are based on paradigms involving dissimilarity metrics. They typically do not take into account relations of antonymy and yield a large number of domain-specific semantic dimensions. Here, using a novel self-organization approach, we construct a low-dimensional, context-independent semantic map of natural language that represents simultaneously synonymy and antonymy. Emergent semantics of the map principal components are clearly identifiable: the first three correspond to the meanings of "good/bad" (valence), "calm/excited" (arousal), and "open/closed" (freedom), respectively. The semantic map is sufficiently robust to allow the automated extraction of synonyms and antonyms not originally in the dictionaries used to construct the map and to predict connotation from their coordinates. The map geometric characteristics include a limited number ( approximately 4) of statistically significant dimensions, a bimodal distribution of the first component, increasing kurtosis of subsequent (unimodal) components, and a U-shaped maximum-spread planar projection. Both the semantic content and the main geometric features of the map are consistent between dictionaries (Microsoft Word and Princeton's WordNet), among Western languages (English, French, German, and Spanish), and with previously established psychometric measures. By defining the semantics of its dimensions, the constructed map provides a foundational metric system for the quantitative analysis of word meaning. Language can be viewed as a cumulative product of human experiences. Therefore, the extracted principal semantic dimensions may be useful to characterize the general semantic dimensions of the content of mental states. This is a fundamental step toward a

  1. Principal semantic components of language and the measurement of meaning.

    Directory of Open Access Journals (Sweden)

    Alexei V Samsonovich

    Full Text Available Metric systems for semantics, or semantic cognitive maps, are allocations of words or other representations in a metric space based on their meaning. Existing methods for semantic mapping, such as Latent Semantic Analysis and Latent Dirichlet Allocation, are based on paradigms involving dissimilarity metrics. They typically do not take into account relations of antonymy and yield a large number of domain-specific semantic dimensions. Here, using a novel self-organization approach, we construct a low-dimensional, context-independent semantic map of natural language that represents simultaneously synonymy and antonymy. Emergent semantics of the map principal components are clearly identifiable: the first three correspond to the meanings of "good/bad" (valence, "calm/excited" (arousal, and "open/closed" (freedom, respectively. The semantic map is sufficiently robust to allow the automated extraction of synonyms and antonyms not originally in the dictionaries used to construct the map and to predict connotation from their coordinates. The map geometric characteristics include a limited number ( approximately 4 of statistically significant dimensions, a bimodal distribution of the first component, increasing kurtosis of subsequent (unimodal components, and a U-shaped maximum-spread planar projection. Both the semantic content and the main geometric features of the map are consistent between dictionaries (Microsoft Word and Princeton's WordNet, among Western languages (English, French, German, and Spanish, and with previously established psychometric measures. By defining the semantics of its dimensions, the constructed map provides a foundational metric system for the quantitative analysis of word meaning. Language can be viewed as a cumulative product of human experiences. Therefore, the extracted principal semantic dimensions may be useful to characterize the general semantic dimensions of the content of mental states. This is a fundamental step

  2. Automatic extraction of ontological relations from Arabic text

    Directory of Open Access Journals (Sweden)

    Mohammed G.H. Al Zamil

    2014-12-01

    The proposed methodology has been designed to analyze Arabic text using lexical semantic patterns of the Arabic language according to a set of features. Next, the features have been abstracted and enriched with formal descriptions for the purpose of generalizing the resulted rules. The rules, then, have formulated a classifier that accepts Arabic text, analyzes it, and then displays related concepts labeled with its designated relationship. Moreover, to resolve the ambiguity of homonyms, a set of machine translation, text mining, and part of speech tagging algorithms have been reused. We performed extensive experiments to measure the effectiveness of our proposed tools. The results indicate that our proposed methodology is promising for automating the process of extracting ontological relations.

  3. Distant supervision for neural relation extraction integrated with word attention and property features.

    Science.gov (United States)

    Qu, Jianfeng; Ouyang, Dantong; Hua, Wen; Ye, Yuxin; Li, Ximing

    2018-04-01

    Distant supervision for neural relation extraction is an efficient approach to extracting massive relations with reference to plain texts. However, the existing neural methods fail to capture the critical words in sentence encoding and meanwhile lack useful sentence information for some positive training instances. To address the above issues, we propose a novel neural relation extraction model. First, we develop a word-level attention mechanism to distinguish the importance of each individual word in a sentence, increasing the attention weights for those critical words. Second, we investigate the semantic information from word embeddings of target entities, which can be developed as a supplementary feature for the extractor. Experimental results show that our model outperforms previous state-of-the-art baselines. Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. GIF Video Sentiment Detection Using Semantic Sequence

    Directory of Open Access Journals (Sweden)

    Dazhen Lin

    2017-01-01

    Full Text Available With the development of social media, an increasing number of people use short videos in social media applications to express their opinions and sentiments. However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem. In this context, we propose a SentiPair Sequence based GIF video sentiment detection approach with two contributions. First, we propose a Synset Forest method to extract sentiment related semantic concepts from WordNet to build a robust SentiPair label set. This approach considers the semantic gap between label words and selects a robust label subset which is related to sentiment. Secondly, we propose a SentiPair Sequence based GIF video sentiment detection approach that learns the semantic sequence to understand the sentiment from GIF videos. Our experiment results on GSO-2016 (GIF Sentiment Ontology data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art middle level sentiment ontology features, Adjective Noun Pairs (ANPs.

  5. Semantic web data warehousing for caGrid.

    Science.gov (United States)

    McCusker, James P; Phillips, Joshua A; González Beltrán, Alejandra; Finkelstein, Anthony; Krauthammer, Michael

    2009-10-01

    The National Cancer Institute (NCI) is developing caGrid as a means for sharing cancer-related data and services. As more data sets become available on caGrid, we need effective ways of accessing and integrating this information. Although the data models exposed on caGrid are semantically well annotated, it is currently up to the caGrid client to infer relationships between the different models and their classes. In this paper, we present a Semantic Web-based data warehouse (Corvus) for creating relationships among caGrid models. This is accomplished through the transformation of semantically-annotated caBIG Unified Modeling Language (UML) information models into Web Ontology Language (OWL) ontologies that preserve those semantics. We demonstrate the validity of the approach by Semantic Extraction, Transformation and Loading (SETL) of data from two caGrid data sources, caTissue and caArray, as well as alignment and query of those sources in Corvus. We argue that semantic integration is necessary for integration of data from distributed web services and that Corvus is a useful way of accomplishing this. Our approach is generalizable and of broad utility to researchers facing similar integration challenges.

  6. Semantic Advertising

    OpenAIRE

    Zamanzadeh, Ben; Ashish, Naveen; Ramakrishnan, Cartic; Zimmerman, John

    2013-01-01

    We present the concept of Semantic Advertising which we see as the future of online advertising. Semantic Advertising is online advertising powered by semantic technology which essentially enables us to represent and reason with concepts and the meaning of things. This paper aims to 1) Define semantic advertising, 2) Place it in the context of broader and more widely used concepts such as the Semantic Web and Semantic Search, 3) Provide a survey of work in related areas such as context matchi...

  7. Semantic and episodic memory in children with temporal lobe epilepsy: do they relate to literacy skills?

    Science.gov (United States)

    Lah, Suncica; Smith, Mary Lou

    2014-01-01

    Children with temporal lobe epilepsy are at risk for deficits in new learning (episodic memory) and literacy skills. Semantic memory deficits and double dissociations between episodic and semantic memory have recently been found in this patient population. In the current study we investigate whether impairments of these 2 distinct memory systems relate to literacy skills. 57 children with unilateral temporal lobe epilepsy completed tests of verbal memory (episodic and semantic) and literacy skills (reading and spelling accuracy, and reading comprehension). For the entire group, semantic memory explained over 30% of variance in each of the literacy domains. Episodic memory explained a significant, but rather small proportion (memory impairments (intact semantic/impaired episodic, intact episodic/impaired semantic) were compared, significant reductions in literacy skills were evident only in children with semantic memory impairments, but not in children with episodic memory impairments relative to the norms and to children with temporal lobe epilepsy who had intact memory. Our study provides the first evidence for differential relations between episodic and semantic memory impairments and literacy skills in children with temporal lobe epilepsy. As such, it highlights the urgent need to consider semantic memory deficits in management of children with temporal lobe epilepsy and undertake further research into the nature of reading difficulties of children with semantic memory impairments.

  8. Age-related differences in recall for words using semantics and prosody.

    Science.gov (United States)

    Sober, Jonathan D; VanWormer, Lisa A; Arruda, James E

    2016-01-01

    The positivity effect is a developmental shift seen in older adults to be increasingly influenced by positive information in areas such as memory, attention, and decision-making. This study is the first to examine the age-related differences of the positivity effect for emotional prosody. Participants heard a factorial combination of words that were semantically positive or negative said with either positive or negative intonation. Results showed a semantic positivity effect for older adults, and a prosody positivity effect for younger adults. Additionally, older adults showed a significant decrease in recall for semantically negative words said in an incongruent prosodically positive tone.

  9. Algorithmic Procedure for Finding Semantically Related Journals.

    Science.gov (United States)

    Pudovkin, Alexander I.; Garfield, Eugene

    2002-01-01

    Using citations, papers and references as parameters a relatedness factor (RF) is computed for a series of journals. Sorting these journals by the RF produces a list of journals most closely related to a specified starting journal. The method appears to select a set of journals that are semantically most similar to the target journal. The…

  10. Measurement of semantic similarity for land use and land cover classification systems

    Science.gov (United States)

    Deng, Dongpo

    2008-12-01

    Land use and land cover (LULC) data is essential to environmental and ecological research. However, semantic heterogeneous of land use and land cover classification are often resulted from different data resources, different cultural contexts, and different utilities. Therefore, there is need to develop a method to measure, compare and integrate between land cover categories. To understand the meaning and the use of terminology from different domains, the common ontology approach is used to acquire information regarding the meaning of terms, and to compare two terms to determine how they might be related. Ontology is a formal specification of a shared conceptualization of a domain of interest. LULC classification system is a ontology. The semantic similarity method is used to compare to entities of three LULC classification systems: CORINE (European Environmental Agency), Oregon State, USA), and Taiwan. The semantic properties and relations firstly have been extracted from their definitions of LULC classification systems. Then semantic properties and relations of categories in three LULC classification systems are mutually compared. The visualization of semantic proximity is finally presented to explore the similarity or dissimilarity of data. This study shows the semantic similarity method efficiently detect semantic distance in three LULC classification systems and find out the semantic similar objects.

  11. Training Of Manual Actions Improves Language Understanding of Semantically-Related Action Sentences

    Directory of Open Access Journals (Sweden)

    Matteo eLocatelli

    2012-12-01

    Full Text Available Conceptual knowledge accessed by language may involve the re-activation of the associated primary sensory-motor processes. Whether these embodied representations are indeed constitutive to conceptual knowledge is hotly debated, particularly since direct evidence that sensory-motor expertise can improve conceptual processing is scarce.In this study, we sought for this crucial piece of evidence, by training naive healthy subjects to perform complex manual actions and by measuring, before and after training, their performance in a semantic language task. 19 participants engaged in 3 weeks of motor training. Each participant was trained in 3 complex manual actions (e.g. origami. Before and after the training period, each subject underwent a series of manual dexterity tests and a semantic language task. The latter consisted of a sentence-picture semantic congruency judgment task, with 6 target congruent sentence-picture pairs (semantically related to the trained manual actions, 6 non-target congruent pairs (semantically unrelated, and 12 filler incongruent pairs.Manual action training induced a significant improvement in all manual dexterity tests, demonstrating the successful acquisition of sensory-motor expertise. In the semantic language task, the reaction times to both target and non-target congruent sentence-image pairs decreased after action training, indicating a more efficient conceptual-semantic processing. Noteworthy, the reaction times for target pairs decreased more than those for non-target pairs, as indicated by the 2x2 interaction. These results were confirmed when controlling for the potential bias of increased frequency of use of target lexical items during manual training.The results of the present study suggest that sensory-motor expertise gained by training of specific manual actions can lead to an improvement of cognitive-linguistic skills related to the specific conceptual-semantic domain associated to the trained actions.

  12. Walking Across Wikipedia: A Scale-Free Network Model of Semantic Memory Retrieval

    Directory of Open Access Journals (Sweden)

    Graham William Thompson

    2014-02-01

    Full Text Available Semantic knowledge has been investigated using both online and offline methods. One common online method is category recall, in which members of a semantic category like animals are retrieved in a given period of time. The order, timing, and number of retrievals are used as assays of semantic memory processes. One common offline method is corpus analysis, in which the structure of semantic knowledge is extracted from texts using co-occurrence or encyclopedic methods. Online measures of semantic processing, as well as offline measures of semantic structure, have yielded data resembling inverse power law distributions. The aim of the present study is to investigate whether these patterns in data might be related. A semantic network model of animal knowledge is formulated on the basis of Wikipedia pages and their overlap in word probability distributions. The network is scale-free, in that node degree is related to node frequency as an inverse power law. A random walk over this network is shown to simulate a number of results from a category recall experiment, including power law-like distributions of inter-response intervals. Results are discussed in terms of theories of semantic structure and processing.

  13. Ontology based heterogeneous materials database integration and semantic query

    Science.gov (United States)

    Zhao, Shuai; Qian, Quan

    2017-10-01

    Materials digital data, high throughput experiments and high throughput computations are regarded as three key pillars of materials genome initiatives. With the fast growth of materials data, the integration and sharing of data is very urgent, that has gradually become a hot topic of materials informatics. Due to the lack of semantic description, it is difficult to integrate data deeply in semantic level when adopting the conventional heterogeneous database integration approaches such as federal database or data warehouse. In this paper, a semantic integration method is proposed to create the semantic ontology by extracting the database schema semi-automatically. Other heterogeneous databases are integrated to the ontology by means of relational algebra and the rooted graph. Based on integrated ontology, semantic query can be done using SPARQL. During the experiments, two world famous First Principle Computational databases, OQMD and Materials Project are used as the integration targets, which show the availability and effectiveness of our method.

  14. Dissociating the effects of semantic grouping and rehearsal strategies on event-related brain potentials.

    Science.gov (United States)

    Schleepen, T M J; Markus, C R; Jonkman, L M

    2014-12-01

    The application of elaborative encoding strategies during learning, such as grouping items on similar semantic categories, increases the likelihood of later recall. Previous studies have suggested that stimuli that encourage semantic grouping strategies had modulating effects on specific ERP components. However, these studies did not differentiate between ERP activation patterns evoked by elaborative working memory strategies like semantic grouping and more simple strategies like rote rehearsal. Identification of neurocognitive correlates underlying successful use of elaborative strategies is important to understand better why certain populations, like children or elderly people, have problems applying such strategies. To compare ERP activation during the application of elaborative versus more simple strategies subjects had to encode either four semantically related or unrelated pictures by respectively applying a semantic category grouping or a simple rehearsal strategy. Another goal was to investigate if maintenance of semantically grouped vs. ungrouped pictures modulated ERP-slow waves differently. At the behavioral level there was only a semantic grouping benefit in terms of faster responding on correct rejections (i.e. when the memory probe stimulus was not part of the memory set). At the neural level, during encoding semantic grouping only had a modest specific modulatory effect on a fronto-central Late Positive Component (LPC), emerging around 650 ms. Other ERP components (i.e. P200, N400 and a second Late Positive Component) that had been earlier related to semantic grouping encoding processes now showed stronger modulation by rehearsal than by semantic grouping. During maintenance semantic grouping had specific modulatory effects on left and right frontal slow wave activity. These results stress the importance of careful control of strategy use when investigating the neural correlates of elaborative encoding. Copyright © 2014 Elsevier B.V. All rights

  15. Semantic Interoperability in Heterogeneous IoT Infrastructure for Healthcare

    Directory of Open Access Journals (Sweden)

    Sohail Jabbar

    2017-01-01

    Full Text Available Interoperability remains a significant burden to the developers of Internet of Things’ Systems. This is due to the fact that the IoT devices are highly heterogeneous in terms of underlying communication protocols, data formats, and technologies. Secondly due to lack of worldwide acceptable standards, interoperability tools remain limited. In this paper, we proposed an IoT based Semantic Interoperability Model (IoT-SIM to provide Semantic Interoperability among heterogeneous IoT devices in healthcare domain. Physicians communicate their patients with heterogeneous IoT devices to monitor their current health status. Information between physician and patient is semantically annotated and communicated in a meaningful way. A lightweight model for semantic annotation of data using heterogeneous devices in IoT is proposed to provide annotations for data. Resource Description Framework (RDF is a semantic web framework that is used to relate things using triples to make it semantically meaningful. RDF annotated patients’ data has made it semantically interoperable. SPARQL query is used to extract records from RDF graph. For simulation of system, we used Tableau, Gruff-6.2.0, and Mysql tools.

  16. An Event Related Potentials Study of Semantic Coherence Effect during Episodic Encoding in Schizophrenia Patients

    Directory of Open Access Journals (Sweden)

    Lâle Battal Merlet

    2018-01-01

    Full Text Available The objective of this electrophysiological study was to investigate the processing of semantic coherence during encoding in relation to episodic memory processes promoted at test, in schizophrenia patients, by using the N400 paradigm. Eighteen schizophrenia patients and 15 healthy participants undertook a recognition memory task. The stimuli consisted of pairs of words either semantically related or unrelated to a given category name (context. During encoding, both groups exhibited an N400 external semantic coherence effect. Healthy controls also showed an N400 internal semantic coherence effect, but this effect was not present in patients. At test, related stimuli were accompanied by an FN400 old/new effect in both groups and by a parietal old/new effect in the control group alone. In the patient group, external semantic coherence effect was associated with FN400, while, in the control group, it was correlated to the parietal old/new effect. Our results indicate that schizophrenia patients can process the contextual information at encoding to enhance familiarity process for related stimuli at test. Therefore, cognitive rehabilitation therapies targeting the implementation of semantic encoding strategies can mobilize familiarity which in turn can overcome the recollection deficit, promoting successful episodic memory performance in schizophrenia patients.

  17. Sieve-based relation extraction of gene regulatory networks from biological literature.

    Science.gov (United States)

    Žitnik, Slavko; Žitnik, Marinka; Zupan, Blaž; Bajec, Marko

    2015-01-01

    Relation extraction is an essential procedure in literature mining. It focuses on extracting semantic relations between parts of text, called mentions. Biomedical literature includes an enormous amount of textual descriptions of biological entities, their interactions and results of related experiments. To extract them in an explicit, computer readable format, these relations were at first extracted manually from databases. Manual curation was later replaced with automatic or semi-automatic tools with natural language processing capabilities. The current challenge is the development of information extraction procedures that can directly infer more complex relational structures, such as gene regulatory networks. We develop a computational approach for extraction of gene regulatory networks from textual data. Our method is designed as a sieve-based system and uses linear-chain conditional random fields and rules for relation extraction. With this method we successfully extracted the sporulation gene regulation network in the bacterium Bacillus subtilis for the information extraction challenge at the BioNLP 2013 conference. To enable extraction of distant relations using first-order models, we transform the data into skip-mention sequences. We infer multiple models, each of which is able to extract different relationship types. Following the shared task, we conducted additional analysis using different system settings that resulted in reducing the reconstruction error of bacterial sporulation network from 0.73 to 0.68, measured as the slot error rate between the predicted and the reference network. We observe that all relation extraction sieves contribute to the predictive performance of the proposed approach. Also, features constructed by considering mention words and their prefixes and suffixes are the most important features for higher accuracy of extraction. Analysis of distances between different mention types in the text shows that our choice of transforming

  18. Semantic types of some generic relation arguments: Detection and evaluation

    NARCIS (Netherlands)

    Katrenko, S.; Adriaans, P.

    2008-01-01

    This paper presents an approach to detection of the semantic types of relation arguments employing the WordNet hierarchy. Using the SemEval-2007 data, we show that the method allows to generalize relation arguments with high precision for such generic relations as Origin-Entity, Content-Container,

  19. Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System

    Directory of Open Access Journals (Sweden)

    Zhenyu Wu

    2017-02-01

    Full Text Available Web of Things (WoT facilitates the discovery and interoperability of Internet of Things (IoT devices in a cyber-physical system (CPS. Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN, it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT framework for CPS (SWoT4CPS. SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.

  20. Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System.

    Science.gov (United States)

    Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

    2017-02-20

    Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.

  1. Semantic Bias in the Acquisition of Relative Clauses in Japanese

    Science.gov (United States)

    Ozeki, Hiromi; Shirai, Yasuhiro

    2010-01-01

    This study analyzes the acquisition of relative clauses in Japanese to determine the semantic and functional characteristics of children's relative clauses in spontaneous speech. Longitudinal data from five Japanese children are analyzed and compared with English data (Diessel & Tomasello, 2000). The results show that the relative clauses produced…

  2. The structure of semantic person memory: evidence from semantic priming in person recognition.

    Science.gov (United States)

    Wiese, Holger

    2011-11-01

    This paper reviews research on the structure of semantic person memory as examined with semantic priming. In this experimental paradigm, a familiarity decision on a target face or written name is usually faster when it is preceded by a related as compared to an unrelated prime. This effect has been shown to be relatively short lived and susceptible to interfering items. Moreover, semantic priming can cross stimulus domains, such that a written name can prime a target face and vice versa. However, it remains controversial whether representations of people are stored in associative networks based on co-occurrence, or in more abstract semantic categories. In line with prominent cognitive models of face recognition, which explain semantic priming by shared semantic information between prime and target, recent research demonstrated that priming could be obtained from purely categorically related, non-associated prime/target pairs. Although strategic processes, such as expectancy and retrospective matching likely contribute, there is also evidence for a non-strategic contribution to priming, presumably related to spreading activation. Finally, a semantic priming effect has been demonstrated in the N400 event-related potential (ERP) component, which may reflect facilitated access to semantic information. It is concluded that categorical relatedness is one organizing principle of semantic person memory. ©2011 The British Psychological Society.

  3. CoRE: A context-aware relation extraction method for relation completion

    KAUST Repository

    Li, Zhixu; Sharaf, Mohamed Abdel Fattah; Sitbon, Laurianne; Du, Xiaoyong; Zhou, Xiaofang

    2014-01-01

    We identify relation completion (RC) as one recurring problem that is central to the success of novel big data applications such as Entity Reconstruction and Data Enrichment. Given a semantic relation {\\cal R}, RC attempts at linking entity pairs between two entity lists under the relation {\\cal R}. To accomplish the RC goals, we propose to formulate search queries for each query entity \\alpha based on some auxiliary information, so that to detect its target entity \\beta from the set of retrieved documents. For instance, a pattern-based method (PaRE) uses extracted patterns as the auxiliary information in formulating search queries. However, high-quality patterns may decrease the probability of finding suitable target entities. As an alternative, we propose CoRE method that uses context terms learned surrounding the expression of a relation as the auxiliary information in formulating queries. The experimental results based on several real-world web data collections demonstrate that CoRE reaches a much higher accuracy than PaRE for the purpose of RC. © 1989-2012 IEEE.

  4. CoRE: A context-aware relation extraction method for relation completion

    KAUST Repository

    Li, Zhixu

    2014-04-01

    We identify relation completion (RC) as one recurring problem that is central to the success of novel big data applications such as Entity Reconstruction and Data Enrichment. Given a semantic relation {\\\\cal R}, RC attempts at linking entity pairs between two entity lists under the relation {\\\\cal R}. To accomplish the RC goals, we propose to formulate search queries for each query entity \\\\alpha based on some auxiliary information, so that to detect its target entity \\\\beta from the set of retrieved documents. For instance, a pattern-based method (PaRE) uses extracted patterns as the auxiliary information in formulating search queries. However, high-quality patterns may decrease the probability of finding suitable target entities. As an alternative, we propose CoRE method that uses context terms learned surrounding the expression of a relation as the auxiliary information in formulating queries. The experimental results based on several real-world web data collections demonstrate that CoRE reaches a much higher accuracy than PaRE for the purpose of RC. © 1989-2012 IEEE.

  5. Effects of relative embodiment in lexical and semantic processing of verbs.

    Science.gov (United States)

    Sidhu, David M; Kwan, Rachel; Pexman, Penny M; Siakaluk, Paul D

    2014-06-01

    Research examining semantic richness effects in visual word recognition has shown that multiple dimensions of meaning are activated in the process of word recognition (e.g., Yap et al., 2012). This research has, however, been limited to nouns. In the present research we extended the semantic richness approach to verb stimuli in order to investigate how verb meanings are represented. We characterized a dimension of relative embodiment for verbs, based on the bodily sense described by Borghi and Cimatti (2010), and collected ratings on that dimension for 687 English verbs. The relative embodiment ratings revealed that bodily experience was judged to be more important to the meanings of some verbs (e.g., dance, breathe) than to others (e.g., evaporate, expect). We then tested the effects of relative embodiment and imageability on verb processing in lexical decision (Experiment 1), action picture naming (Experiment 2), and syntactic classification (Experiment 3). In all three experiments results showed facilitatory effects of relative embodiment, but not imageability: latencies were faster for relatively more embodied verbs, even after several other lexical variables were controlled. The results suggest that relative embodiment is an important aspect of verb meaning, and that the semantic richness approach holds promise as a strategy for investigating other aspects of verb meaning. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Lexical-Semantic Processing and Reading: Relations between Semantic Priming, Visual Word Recognition and Reading Comprehension

    Science.gov (United States)

    Nobre, Alexandre de Pontes; de Salles, Jerusa Fumagalli

    2016-01-01

    The aim of this study was to investigate relations between lexical-semantic processing and two components of reading: visual word recognition and reading comprehension. Sixty-eight children from private schools in Porto Alegre, Brazil, from 7 to 12 years, were evaluated. Reading was assessed with a word/nonword reading task and a reading…

  7. Semantic types of some generic relation arguments: Detection and evaluation

    OpenAIRE

    Katrenko, S.; Adriaans, P.

    2008-01-01

    This paper presents an approach to detection of the semantic types of relation arguments employing the WordNet hierarchy. Using the SemEval-2007 data, we show that the method allows to generalize relation arguments with high precision for such generic relations as Origin-Entity, Content-Container, Instrument-Agency and some other.

  8. Semantic Relations between Legal Terms. A Case Study of the Intralingual Relation of Synonymy

    Directory of Open Access Journals (Sweden)

    Matulewska Aleksandra

    2016-06-01

    Full Text Available The author intends to present a possibility of parametrising legal terminology in order to reveal semantic and systemic relations at the intralingual and interlingual levels. The scope of the research comprises selected legal terminology from the following legal systems: Polish, British, American and European Union. The research methods used include: (i the analysis of comparable texts, (ii the method of parametrisation of the legal linguistic reality, (iii the concept of adjusting translation to the communicative needs and requirements of the recipient community. The research hypothesis is that parametrisation of legal terminology in respect of semantic and systemic relations may be a useful tool in organising and comparing terminology for the purpose of legal translation. First the relation of synonymy binding terms at the intralingual and interlingual levels in the light of systemic and genre-related relations is discussed. The proposal is illustrated with examples of legal terms and the networks of relations binding them in English and Polish. The conclusions are that such an approach is systematic and provides a translator with information necessary to render communicatively efficient translations.

  9. PREDOSE: a semantic web platform for drug abuse epidemiology using social media.

    Science.gov (United States)

    Cameron, Delroy; Smith, Gary A; Daniulaityte, Raminta; Sheth, Amit P; Dave, Drashti; Chen, Lu; Anand, Gaurish; Carlson, Robert; Watkins, Kera Z; Falck, Russel

    2013-12-01

    The role of social media in biomedical knowledge mining, including clinical, medical and healthcare informatics, prescription drug abuse epidemiology and drug pharmacology, has become increasingly significant in recent years. Social media offers opportunities for people to share opinions and experiences freely in online communities, which may contribute information beyond the knowledge of domain professionals. This paper describes the development of a novel semantic web platform called PREDOSE (PREscription Drug abuse Online Surveillance and Epidemiology), which is designed to facilitate the epidemiologic study of prescription (and related) drug abuse practices using social media. PREDOSE uses web forum posts and domain knowledge, modeled in a manually created Drug Abuse Ontology (DAO--pronounced dow), to facilitate the extraction of semantic information from User Generated Content (UGC), through combination of lexical, pattern-based and semantics-based techniques. In a previous study, PREDOSE was used to obtain the datasets from which new knowledge in drug abuse research was derived. Here, we report on various platform enhancements, including an updated DAO, new components for relationship and triple extraction, and tools for content analysis, trend detection and emerging patterns exploration, which enhance the capabilities of the PREDOSE platform. Given these enhancements, PREDOSE is now more equipped to impact drug abuse research by alleviating traditional labor-intensive content analysis tasks. Using custom web crawlers that scrape UGC from publicly available web forums, PREDOSE first automates the collection of web-based social media content for subsequent semantic annotation. The annotation scheme is modeled in the DAO, and includes domain specific knowledge such as prescription (and related) drugs, methods of preparation, side effects, and routes of administration. The DAO is also used to help recognize three types of data, namely: (1) entities, (2

  10. Structural similarities between brain and linguistic data provide evidence of semantic relations in the brain.

    Directory of Open Access Journals (Sweden)

    Colleen E Crangle

    Full Text Available This paper presents a new method of analysis by which structural similarities between brain data and linguistic data can be assessed at the semantic level. It shows how to measure the strength of these structural similarities and so determine the relatively better fit of the brain data with one semantic model over another. The first model is derived from WordNet, a lexical database of English compiled by language experts. The second is given by the corpus-based statistical technique of latent semantic analysis (LSA, which detects relations between words that are latent or hidden in text. The brain data are drawn from experiments in which statements about the geography of Europe were presented auditorily to participants who were asked to determine their truth or falsity while electroencephalographic (EEG recordings were made. The theoretical framework for the analysis of the brain and semantic data derives from axiomatizations of theories such as the theory of differences in utility preference. Using brain-data samples from individual trials time-locked to the presentation of each word, ordinal relations of similarity differences are computed for the brain data and for the linguistic data. In each case those relations that are invariant with respect to the brain and linguistic data, and are correlated with sufficient statistical strength, amount to structural similarities between the brain and linguistic data. Results show that many more statistically significant structural similarities can be found between the brain data and the WordNet-derived data than the LSA-derived data. The work reported here is placed within the context of other recent studies of semantics and the brain. The main contribution of this paper is the new method it presents for the study of semantics and the brain and the focus it permits on networks of relations detected in brain data and represented by a semantic model.

  11. Geospatial semantic web

    CERN Document Server

    Zhang, Chuanrong; Li, Weidong

    2015-01-01

    This book covers key issues related to Geospatial Semantic Web, including geospatial web services for spatial data interoperability; geospatial ontology for semantic interoperability; ontology creation, sharing, and integration; querying knowledge and information from heterogeneous data source; interfaces for Geospatial Semantic Web, VGI (Volunteered Geographic Information) and Geospatial Semantic Web; challenges of Geospatial Semantic Web; and development of Geospatial Semantic Web applications. This book also describes state-of-the-art technologies that attempt to solve these problems such as WFS, WMS, RDF, OWL, and GeoSPARQL, and demonstrates how to use the Geospatial Semantic Web technologies to solve practical real-world problems such as spatial data interoperability.

  12. Semantics of Kinship Terms in Tamil from the Semantic Typology Point of View

    Directory of Open Access Journals (Sweden)

    Анна Александровна Смирнитская

    2016-12-01

    Full Text Available In this article the author examines the lexical-semantic group “kinship terms” in Tamil, applying the attainments of modern semantic typology and the theory of semantic derivation. The kinship terms describing nuclear and extended family are explored. The “semantic shift” relation between two different meanings is established if such relation is realized by synchronous polysemy in one lexeme, semantic derivation, diachronic semantic change, cognates or some other means. The starting point of the study is the typological data from the DatSemShift catalogue of semantic shifts in languages of the world developed by a group of researchers under the guidance of Anna A. Zalizniak in the Institute of Linguistics, RAS. We verify the presence of semantic shifts described in the Database in Tamil. Also, we propose new semantic shifts specific only for this language. We confirm the presence of semantic relation of the studied type among the meanings with English “labels”: father - parents, girl - daughter, to deliver (a child - parents, - child, old woman - wife, owner - wife and others. The data also allows the assumption that the same relation exists between the meanings: old - grandfather, earth - mother, son - courage, unripe - son and others. The meanings of this field are the sources of semantic movements to abstract notions, lexicon of posession, forms of address and others; in addition many inner semantic relations inside this field are revealed. The meanings covering the nuclear part of the kinship system participate in universal semantic shifts described in the DatSemShift catalogue, while the meanings from collateral branches of this bifurcative kinship system (uncle, aunt turn out to be incomparable with kinship terms from indo-european lineal systems. Their meanings can be included in the DatSemShift catalogue only with an indication of system specifics. The information about semantic shifts can be useful for

  13. Spatial and Semantic Processing between Audition and Vision: An Event-Related Potential Study

    Directory of Open Access Journals (Sweden)

    Xiaoxi Chen

    2011-10-01

    Full Text Available Using a crossmodal priming paradigm, this study investigated how the brain bound the spatial and semantic features in multisensory processing. The visual stimuli (pictures of animals were presented after the auditory stimuli (sounds of animals, and the stimuli from different modalities may match spatially (or semantically or not. Participants were required to detect the head orientation of the visual target (an oddball paradigm. The event-related potentials (ERPs to the visual stimuli was enhanced by spatial attention (150–170 ms irrespectively of semantic information. The early crossmodal attention effect for the visual stimuli was more negative in the spatial-congruent condition than in the spatial-incongruent condition. By contrast, the later effects of spatial ERPs were significant only for the semantic- congruent condition (250–300 ms. These findings indicated that spatial attention modulated early visual processing, and semantic and spatial features were simultaneously used to orient attention and modulate later processing stages.

  14. Differences in Processing of Taxonomic and Sequential Relations in Semantic Memory: An fMRI Investigation

    Science.gov (United States)

    Kuchinke, Lars; van der Meer, Elke; Krueger, Frank

    2009-01-01

    Conceptual knowledge of our world is represented in semantic memory in terms of concepts and semantic relations between concepts. We used functional magnetic resonance imaging (fMRI) to examine the cortical regions underlying the processing of sequential and taxonomic relations. Participants were presented verbal cues and performed three tasks:…

  15. Assessing semantic similarity of texts - Methods and algorithms

    Science.gov (United States)

    Rozeva, Anna; Zerkova, Silvia

    2017-12-01

    Assessing the semantic similarity of texts is an important part of different text-related applications like educational systems, information retrieval, text summarization, etc. This task is performed by sophisticated analysis, which implements text-mining techniques. Text mining involves several pre-processing steps, which provide for obtaining structured representative model of the documents in a corpus by means of extracting and selecting the features, characterizing their content. Generally the model is vector-based and enables further analysis with knowledge discovery approaches. Algorithms and measures are used for assessing texts at syntactical and semantic level. An important text-mining method and similarity measure is latent semantic analysis (LSA). It provides for reducing the dimensionality of the document vector space and better capturing the text semantics. The mathematical background of LSA for deriving the meaning of the words in a given text by exploring their co-occurrence is examined. The algorithm for obtaining the vector representation of words and their corresponding latent concepts in a reduced multidimensional space as well as similarity calculation are presented.

  16. Semantic Network Analysis on Terms related Mantle in Earth Science 2 Textbooks of Korea

    Science.gov (United States)

    Chung, Duk Ho; reum Cho, Ah; Park, Seon Ok

    2016-04-01

    The purpose of this study is to demonstrate if freshmen's cognitive frame about 'Crisis of the Earth' upon taking the Earth science 1 in high school reflects the school curriculum. The data was collected from 67 freshmen who'd graduated high school in formal education. They expressed 'Crisis of the Earth' as a painting with explanation and then we extracted units of meaning from paintings, respectively. We analyzed the words and frame using the Semantic Network Analysis. The result is as follows; First, as every participant forms the cognitive frame for the crisis of the Earth, it is shown that they connect each part which that composes the global environment and realize it as the changing relation with interaction. Secondly, forming a cognitive frame regarding crisis of the Earth, both groups connect it with human endeavor. Especially, it seems that the group of participants who finished Earth Science I fully reflects the course of the formal education. It is necessary to make the students recognize it from a universal point of view, not only from the Earth. Also, much effort is required in order to enlighten about the appropriateness regarding problem-solving of the Earth and expand their mind as time changes. Keywords : Earth ScienceⅠ, cognitive frame, crisis of the earth, semantic network analysis

  17. Effects of semantic relatedness on age-related associative memory deficits: the role of theta oscillations.

    Science.gov (United States)

    Crespo-Garcia, Maite; Cantero, Jose L; Atienza, Mercedes

    2012-07-16

    Growing evidence suggests that age-related deficits in associative memory are alleviated when the to-be-associated items are semantically related. Here we investigate whether this beneficial effect of semantic relatedness is paralleled by spatio-temporal changes in cortical EEG dynamics during incidental encoding. Young and older adults were presented with faces at a particular spatial location preceded by a biographical cue that was either semantically related or unrelated. As expected, automatic encoding of face-location associations benefited from semantic relatedness in the two groups of age. This effect correlated with increased power of theta oscillations over medial and anterior lateral regions of the prefrontal cortex (PFC) and lateral regions of the posterior parietal cortex (PPC) in both groups. But better-performing elders also showed increased brain-behavior correlation in the theta band over the right inferior frontal gyrus (IFG) as compared to young adults. Semantic relatedness was, however, insufficient to fully eliminate age-related differences in associative memory. In line with this finding, poorer-performing elders relative to young adults showed significant reductions of theta power in the left IFG that were further predictive of behavioral impairment in the recognition task. All together, these results suggest that older adults benefit less than young adults from executive processes during encoding mainly due to neural inefficiency over regions of the left ventrolateral prefrontal cortex (VLPFC). But this associative deficit may be partially compensated for by engaging preexistent semantic knowledge, which likely leads to an efficient recruitment of attentional and integration processes supported by the left PPC and left anterior PFC respectively, together with neural compensatory mechanisms governed by the right VLPFC. Copyright © 2012 Elsevier Inc. All rights reserved.

  18. Semantic Similarity between Web Documents Using Ontology

    Science.gov (United States)

    Chahal, Poonam; Singh Tomer, Manjeet; Kumar, Suresh

    2018-06-01

    The World Wide Web is the source of information available in the structure of interlinked web pages. However, the procedure of extracting significant information with the assistance of search engine is incredibly critical. This is for the reason that web information is written mainly by using natural language, and further available to individual human. Several efforts have been made in semantic similarity computation between documents using words, concepts and concepts relationship but still the outcome available are not as per the user requirements. This paper proposes a novel technique for computation of semantic similarity between documents that not only takes concepts available in documents but also relationships that are available between the concepts. In our approach documents are being processed by making ontology of the documents using base ontology and a dictionary containing concepts records. Each such record is made up of the probable words which represents a given concept. Finally, document ontology's are compared to find their semantic similarity by taking the relationships among concepts. Relevant concepts and relations between the concepts have been explored by capturing author and user intention. The proposed semantic analysis technique provides improved results as compared to the existing techniques.

  19. Semantic Similarity between Web Documents Using Ontology

    Science.gov (United States)

    Chahal, Poonam; Singh Tomer, Manjeet; Kumar, Suresh

    2018-03-01

    The World Wide Web is the source of information available in the structure of interlinked web pages. However, the procedure of extracting significant information with the assistance of search engine is incredibly critical. This is for the reason that web information is written mainly by using natural language, and further available to individual human. Several efforts have been made in semantic similarity computation between documents using words, concepts and concepts relationship but still the outcome available are not as per the user requirements. This paper proposes a novel technique for computation of semantic similarity between documents that not only takes concepts available in documents but also relationships that are available between the concepts. In our approach documents are being processed by making ontology of the documents using base ontology and a dictionary containing concepts records. Each such record is made up of the probable words which represents a given concept. Finally, document ontology's are compared to find their semantic similarity by taking the relationships among concepts. Relevant concepts and relations between the concepts have been explored by capturing author and user intention. The proposed semantic analysis technique provides improved results as compared to the existing techniques.

  20. Subliminal semantic priming in speech.

    Directory of Open Access Journals (Sweden)

    Jérôme Daltrozzo

    Full Text Available Numerous studies have reported subliminal repetition and semantic priming in the visual modality. We transferred this paradigm to the auditory modality. Prime awareness was manipulated by a reduction of sound intensity level. Uncategorized prime words (according to a post-test were followed by semantically related, unrelated, or repeated target words (presented without intensity reduction and participants performed a lexical decision task (LDT. Participants with slower reaction times in the LDT showed semantic priming (faster reaction times for semantically related compared to unrelated targets and negative repetition priming (slower reaction times for repeated compared to semantically related targets. This is the first report of semantic priming in the auditory modality without conscious categorization of the prime.

  1. Arabic web pages clustering and annotation using semantic class features

    Directory of Open Access Journals (Sweden)

    Hanan M. Alghamdi

    2014-12-01

    Full Text Available To effectively manage the great amount of data on Arabic web pages and to enable the classification of relevant information are very important research problems. Studies on sentiment text mining have been very limited in the Arabic language because they need to involve deep semantic processing. Therefore, in this paper, we aim to retrieve machine-understandable data with the help of a Web content mining technique to detect covert knowledge within these data. We propose an approach to achieve clustering with semantic similarities. This approach comprises integrating k-means document clustering with semantic feature extraction and document vectorization to group Arabic web pages according to semantic similarities and then show the semantic annotation. The document vectorization helps to transform text documents into a semantic class probability distribution or semantic class density. To reach semantic similarities, the approach extracts the semantic class features and integrates them into the similarity weighting schema. The quality of the clustering result has evaluated the use of the purity and the mean intra-cluster distance (MICD evaluation measures. We have evaluated the proposed approach on a set of common Arabic news web pages. We have acquired favorable clustering results that are effective in minimizing the MICD, expanding the purity and lowering the runtime.

  2. Age-related vulnerability in the neural systems supporting semantic processing

    Directory of Open Access Journals (Sweden)

    Jonathan E Peelle

    2013-09-01

    Full Text Available Our ability to form abstract representations of objects in semantic memory is crucial to language and thought. The utility of this information relies both on the representations of sensory-motor feature knowledge stored in long-term memory and the executive processes required to retrieve, manipulate, and evaluate this semantic knowledge in a task-relevant manner. These complementary components of semantic memory can be differentially impacted by aging. We investigated semantic processing in normal aging using functional magnetic resonance imaging (fMRI. Young and older adults were asked to judge whether two printed object names match on a particular feature (for example, whether a tomato and strawberry have the same color. The task thus required both retrieval of relevant visual feature knowledge of object concepts and evaluating this information. Objects were drawn from either natural kinds or manufactured objects, and were queried on either color or shape in a factorial design. Behaviorally, all subjects performed well, but older adults could be divided into those whose performance matched that of young adults (better performers and those whose performance was worse (poorer performers. All subjects activated several cortical regions while performing this task, including bilateral inferior and lateral temporal cortex and left frontal and prefrontal cortex. Better performing older adults showed increased overall activity in bilateral premotor cortex and left lateral occipital cortex compared to young adults, and increased activity in these brain regions relative to poorer performing older adults who also showed gray matter atrophy in premotor cortex. These findings highlight the contribution of domain-general executive processing brain regions to semantic memory, and illustrate differences in how these regions are recruited in healthy older adults.

  3. Exploiting graph kernels for high performance biomedical relation extraction.

    Science.gov (United States)

    Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

    2018-01-30

    Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM

  4. Spatial-Temporal Junction Extraction and Semantic Interpretation

    DEFF Research Database (Denmark)

    Simonsen, Kasper Broegaard; Thorsted Nielsen, Mads; Pilz, Florian

    2009-01-01

    This article describes a novel junction descriptor that encodes junctions’ semantic information in terms incoming lines’ orientations, both in 2D and 3D. A Kalman filter process is used to reduce the effect of local noise on the descriptor's error and to track the features. The improvement gained...

  5. Semantic Approaches for Knowledge Discovery and Retrieval in Biomedicine

    DEFF Research Database (Denmark)

    Wilkowski, Bartlomiej

    This thesis discusses potential applications of semantics to the recent literaturebased informatics systems to facilitate knowledge discovery, hypothesis generation, and literature retrieval in the domain of biomedicine. The approaches presented herein make use of semantic information extracted...

  6. Topic structure affects semantic integration: evidence from event-related potentials.

    Science.gov (United States)

    Yang, Xiaohong; Chen, Xuhai; Chen, Shuang; Xu, Xiaoying; Yang, Yufang

    2013-01-01

    This study investigated whether semantic integration in discourse context could be influenced by topic structure using event-related brain potentials. Participants read discourses in which the last sentence contained a critical word that was either congruent or incongruent with the topic established in the first sentence. The intervening sentences between the first and the last sentence of the discourse either maintained or shifted the original topic. Results showed that incongruent words in topic-maintained discourses elicited an N400 effect that was broadly distributed over the scalp while those in topic-shifted discourses elicited an N400 effect that was lateralized to the right hemisphere and localized over central and posterior areas. Moreover, a late positivity effect was only elicited by incongruent words in topic-shifted discourses, but not in topic-maintained discourses. This suggests an important role for discourse structure in semantic integration, such that compared with topic-maintained discourses, the complexity of discourse structure in topic-shifted condition reduces the initial stage of semantic integration and enhances the later stage in which a mental representation is updated.

  7. Getting connected: Both associative and semantic links structure semantic memory for newly learned persons.

    Science.gov (United States)

    Wiese, Holger; Schweinberger, Stefan R

    2015-01-01

    The present study examined whether semantic memory for newly learned people is structured by visual co-occurrence, shared semantics, or both. Participants were trained with pairs of simultaneously presented (i.e., co-occurring) preexperimentally unfamiliar faces, which either did or did not share additionally provided semantic information (occupation, place of living, etc.). Semantic information could also be shared between faces that did not co-occur. A subsequent priming experiment revealed faster responses for both co-occurrence/no shared semantics and no co-occurrence/shared semantics conditions, than for an unrelated condition. Strikingly, priming was strongest in the co-occurrence/shared semantics condition, suggesting additive effects of these factors. Additional analysis of event-related brain potentials yielded priming in the N400 component only for combined effects of visual co-occurrence and shared semantics, with more positive amplitudes in this than in the unrelated condition. Overall, these findings suggest that both semantic relatedness and visual co-occurrence are important when novel information is integrated into person-related semantic memory.

  8. Semantic metrics

    OpenAIRE

    Hu, Bo; Kalfoglou, Yannis; Dupplaw, David; Alani, Harith; Lewis, Paul; Shadbolt, Nigel

    2006-01-01

    In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can be boiled down to one fundamental operation: computing the similarity and/or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a...

  9. Semantic Analysis of Verbal Collocations with Lexical Functions

    CERN Document Server

    Gelbukh, Alexander

    2013-01-01

    This book is written for both linguists and computer scientists working in the field of artificial intelligence as well as to anyone interested in intelligent text processing. Lexical function is a concept that formalizes semantic and syntactic relations between lexical units. Collocational relation is a type of institutionalized lexical relations which holds between the base and its partner in a collocation. Knowledge of collocation is important for natural language processing because collocation comprises the restrictions on how words can be used together. The book shows how collocations can be annotated with lexical functions in a computer readable dictionary - allowing their precise semantic analysis in texts and their effective use in natural language applications including parsers, high quality machine translation, periphrasis system and computer-aided learning of lexica. The books shows how to extract collocations from corpora and annotate them with lexical functions automatically. To train algorithms,...

  10. Do U Txt? Event-Related Potentials to Semantic Anomalies in Standard and Texted English

    Science.gov (United States)

    Berger, Natalie I.; Coch, Donna

    2010-01-01

    Texted English is a hybrid, technology-based language derived from standard English modified to facilitate ease of communication via instant and text messaging. We compared semantic processing of texted and standard English sentences by recording event-related potentials in a classic semantic incongruity paradigm designed to elicit an N400 effect.…

  11. Enhancing acronym/abbreviation knowledge bases with semantic information.

    Science.gov (United States)

    Torii, Manabu; Liu, Hongfang

    2007-10-11

    In the biomedical domain, a terminology knowledge base that associates acronyms/abbreviations (denoted as SFs) with the definitions (denoted as LFs) is highly needed. For the construction such terminology knowledge base, we investigate the feasibility to build a system automatically assigning semantic categories to LFs extracted from text. Given a collection of pairs (SF,LF) derived from text, we i) assess the coverage of LFs and pairs (SF,LF) in the UMLS and justify the need of a semantic category assignment system; and ii) automatically derive name phrases annotated with semantic category and construct a system using machine learning. Utilizing ADAM, an existing collection of (SF,LF) pairs extracted from MEDLINE, our system achieved an f-measure of 87% when assigning eight UMLS-based semantic groups to LFs. The system has been incorporated into a web interface which integrates SF knowledge from multiple SF knowledge bases. Web site: http://gauss.dbb.georgetown.edu/liblab/SFThesurus.

  12. Recommender System for E-Learning Based on Semantic Relatedness of Concepts

    Directory of Open Access Journals (Sweden)

    Mao Ye

    2015-08-01

    Full Text Available Digital publishing resources contain a lot of useful and authoritative knowledge. It may be necessary to reorganize the resources by concepts and recommend the related concepts for e-learning. A recommender system is presented in this paper based on the semantic relatedness of concepts computed by texts from digital publishing resources. Firstly, concepts are extracted from encyclopedias. Information in digital publishing resources is then reorganized by concepts. Secondly, concept vectors are generated by skip-gram model and semantic relatedness between concepts is measured according to the concept vectors. As a result, the related concepts and associated information can be recommended to users by the semantic relatedness for learning or reading. History data or users’ preferences data are not needed for recommendation in a specific domain. The technique may not be language-specific. The method shows potential usability for e-learning in a specific domain.

  13. Montague semantics

    NARCIS (Netherlands)

    Janssen, T.M.V.

    2012-01-01

    Montague semantics is a theory of natural language semantics and of its relation with syntax. It was originally developed by the logician Richard Montague (1930-1971) and subsequently modified and extended by linguists, philosophers, and logicians. The most important features of the theory are its

  14. Varieties of semantic 'access' deficit in Wernicke's aphasia and semantic aphasia.

    Science.gov (United States)

    Thompson, Hannah E; Robson, Holly; Lambon Ralph, Matthew A; Jefferies, Elizabeth

    2015-12-01

    Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke's aphasia, associated with poor auditory-verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic 'access' deficit, as opposed to the 'storage' deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of 'access' impairment-related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke's aphasia). We used a case series design to compare patients with Wernicke's aphasia and those with semantic aphasia on Warrington's paradigmatic assessment of semantic 'access' deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic 'blocking' effects). Patients with Wernicke's aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability-one that mapped onto classical 'syndromes' and one that did not-predicted aspects of the semantic 'access' deficit. Both semantic aphasia and Wernicke's aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke's aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially 'beneficial' effects of stimulus repetition: cases with

  15. Geographic Knowledge Extraction and Semantic Similarity in OpenStreetMap

    OpenAIRE

    Ballatore, Andrea; Bertolotto, Michela; Wilson, David C.

    2012-01-01

    In recent years, a web phenomenon known as Volunteered Geographic Information (VGI) has produced large crowdsourced geographic data sets. OpenStreetMap (OSM), the leading VGI project, aims at building an open-content world map through user contributions. OSM semantics consists of a set of properties (called 'tags') describing geographic classes, whose usage is defined by project contributors on a dedicated Wiki website. Because of its simple and open semantic structure, the OSM approach often...

  16. Bridging the semantic gap in sports

    Science.gov (United States)

    Li, Baoxin; Errico, James; Pan, Hao; Sezan, M. Ibrahim

    2003-01-01

    One of the major challenges facing current media management systems and the related applications is the so-called "semantic gap" between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs. The framework is based on a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. An MPEG-7 compliant prototype browsing system has been implemented to demonstrate semantic retrieval and summarization of sports video.

  17. Considering the role of semantic memory in episodic future thinking: evidence from semantic dementia.

    Science.gov (United States)

    Irish, Muireann; Addis, Donna Rose; Hodges, John R; Piguet, Olivier

    2012-07-01

    Semantic dementia is a progressive neurodegenerative condition characterized by the profound and amodal loss of semantic memory in the context of relatively preserved episodic memory. In contrast, patients with Alzheimer's disease typically display impairments in episodic memory, but with semantic deficits of a much lesser magnitude than in semantic dementia. Our understanding of episodic memory retrieval in these cohorts has greatly increased over the last decade, however, we know relatively little regarding the ability of these patients to imagine and describe possible future events, and whether episodic future thinking is mediated by divergent neural substrates contingent on dementia subtype. Here, we explored episodic future thinking in patients with semantic dementia (n=11) and Alzheimer's disease (n=11), in comparison with healthy control participants (n=10). Participants completed a battery of tests designed to probe episodic and semantic thinking across past and future conditions, as well as standardized tests of episodic and semantic memory. Further, all participants underwent magnetic resonance imaging. Despite their relatively intact episodic retrieval for recent past events, the semantic dementia cohort showed significant impairments for episodic future thinking. In contrast, the group with Alzheimer's disease showed parallel deficits across past and future episodic conditions. Voxel-based morphometry analyses confirmed that atrophy in the left inferior temporal gyrus and bilateral temporal poles, regions strongly implicated in semantic memory, correlated significantly with deficits in episodic future thinking in semantic dementia. Conversely, episodic future thinking performance in Alzheimer's disease correlated with atrophy in regions associated with episodic memory, namely the posterior cingulate, parahippocampal gyrus and frontal pole. These distinct neuroanatomical substrates contingent on dementia group were further qualified by correlational

  18. Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases.

    Science.gov (United States)

    Wollbrett, Julien; Larmande, Pierre; de Lamotte, Frédéric; Ruiz, Manuel

    2013-04-15

    In recent years, a large amount of "-omics" data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic.

  19. Basic semantics of product sounds

    NARCIS (Netherlands)

    Özcan Vieira, E.; Van Egmond, R.

    2012-01-01

    Product experience is a result of sensory and semantic experiences with product properties. In this paper, we focus on the semantic attributes of product sounds and explore the basic components for product sound related semantics using a semantic differential paradigmand factor analysis. With two

  20. Universal Dimensions of Meaning Derived from Semantic Relations among Words and Senses: Mereological Completeness vs. Ontological Generality

    Directory of Open Access Journals (Sweden)

    Alexei V. Samsonovich

    2014-07-01

    Full Text Available A key to semantic analysis is a precise and practically useful definition of meaning that is general for all domains of knowledge. We previously introduced the notion of weak semantic map: a metric space allocating concepts along their most general (universal semantic characteristics while at the same time ignoring other, domain-specific aspects of their meanings. Here we address questions of the number, quality, and mutual independence of the weak semantic dimensions. Specifically, we employ semantic relationships not previously used for weak semantic mapping, such as holonymy/meronymy (“is-part/member-of”, and we compare maps constructed from word senses to those constructed from words. We show that the “completeness” dimension derived from the holonym/meronym relation is independent of, and practically orthogonal to, the “abstractness” dimension derived from the hypernym-hyponym (“is-a” relation, while both dimensions are orthogonal to the maps derived from synonymy and antonymy. Interestingly, the choice of using relations among words vs. senses implies a non-trivial trade-off between rich and unambiguous information due to homonymy and polysemy. The practical utility of the new and prior dimensions is illustrated by the automated evaluation of different kinds of documents. Residual analysis of available linguistic resources, such as WordNet, suggests that the number of universal semantic dimensions representable in natural language may be finite. Their complete characterization, as well as the extension of results to non-linguistic materials, remains an open challenge.

  1. Age-related changes in ERP components of semantic and syntactic processing in a verb final language

    Directory of Open Access Journals (Sweden)

    Jee Eun Sung

    2014-04-01

    Both syntactic and semantic violations elicited negativity effects at 300-500ms time window, and the negativity effects were slightly attenuated in the elderly group. The results suggested that Korean speakers may process a syntactic component of a case marker under the semantic frame integration, eliciting the negativity effects associated with semantic violations. Elderly adults showed attenuated effects compared to the young group, indicating age-related changes emerged during real-time sentence processing.

  2. Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases

    Science.gov (United States)

    2013-01-01

    Background In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. Results We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. Conclusions BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic. PMID:23586394

  3. AMATCHMETHOD BASED ON LATENT SEMANTIC ANALYSIS FOR EARTHQUAKEHAZARD EMERGENCY PLAN

    Directory of Open Access Journals (Sweden)

    D. Sun

    2017-09-01

    Full Text Available The structure of the emergency plan on earthquake is complex, and it’s difficult for decision maker to make a decision in a short time. To solve the problem, this paper presents a match method based on Latent Semantic Analysis (LSA. After the word segmentation preprocessing of emergency plan, we carry out keywords extraction according to the part-of-speech and the frequency of words. Then through LSA, we map the documents and query information to the semantic space, and calculate the correlation of documents and queries by the relation between vectors. The experiments results indicate that the LSA can improve the accuracy of emergency plan retrieval efficiently.

  4. Amatchmethod Based on Latent Semantic Analysis for Earthquakehazard Emergency Plan

    Science.gov (United States)

    Sun, D.; Zhao, S.; Zhang, Z.; Shi, X.

    2017-09-01

    The structure of the emergency plan on earthquake is complex, and it's difficult for decision maker to make a decision in a short time. To solve the problem, this paper presents a match method based on Latent Semantic Analysis (LSA). After the word segmentation preprocessing of emergency plan, we carry out keywords extraction according to the part-of-speech and the frequency of words. Then through LSA, we map the documents and query information to the semantic space, and calculate the correlation of documents and queries by the relation between vectors. The experiments results indicate that the LSA can improve the accuracy of emergency plan retrieval efficiently.

  5. Implicit Phonological and Semantic Processing in Children with Developmental Dyslexia: Evidence from Event-Related Potentials

    Science.gov (United States)

    Jednorog, K.; Marchewka, A.; Tacikowski, P.; Grabowska, A.

    2010-01-01

    Dyslexia is characterized by a core phonological deficit, although recent studies indicate that semantic impairment also contributes to this condition. In this study, event-related potentials (ERP) were used to examine whether the N400 wave in dyslexic children is modulated by phonological or semantic priming, similarly to age-matched controls.…

  6. Post-processing of Deep Web Information Extraction Based on Domain Ontology

    Directory of Open Access Journals (Sweden)

    PENG, T.

    2013-11-01

    Full Text Available Many methods are utilized to extract and process query results in deep Web, which rely on the different structures of Web pages and various designing modes of databases. However, some semantic meanings and relations are ignored. So, in this paper, we present an approach for post-processing deep Web query results based on domain ontology which can utilize the semantic meanings and relations. A block identification model (BIM based on node similarity is defined to extract data blocks that are relevant to specific domain after reducing noisy nodes. Feature vector of domain books is obtained by result set extraction model (RSEM based on vector space model (VSM. RSEM, in combination with BIM, builds the domain ontology on books which can not only remove the limit of Web page structures when extracting data information, but also make use of semantic meanings of domain ontology. After extracting basic information of Web pages, a ranking algorithm is adopted to offer an ordered list of data records to users. Experimental results show that BIM and RSEM extract data blocks and build domain ontology accurately. In addition, relevant data records and basic information are extracted and ranked. The performances precision and recall show that our proposed method is feasible and efficient.

  7. Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System

    OpenAIRE

    Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

    2017-01-01

    Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships betwe...

  8. A generalized notion of semantic independence

    DEFF Research Database (Denmark)

    Fränzle, Martin; Stengel, Bernhard von; Wittmüss, Arne

    1995-01-01

    For programs represented semantically as relations, a concept of semantic independence is defined that is more general than previously stated notions. It allows for shared input variables and irrelevant interference due to nondeterminism.......For programs represented semantically as relations, a concept of semantic independence is defined that is more general than previously stated notions. It allows for shared input variables and irrelevant interference due to nondeterminism....

  9. On the Translation of Semantic Relations: an empirical study

    Directory of Open Access Journals (Sweden)

    Louise Denver

    2002-01-01

    Full Text Available In this article, the transfer of semantic relations between propositions is discussed based on a pilot study carried out for didactic purposes at the Copenhagen Business School. The relations studied were unmarked in the source text (ST and the research aimed at investigating to what extent the translation of textual cohesion is the object of mental processing by semi-professional opt for a strategy involving the explicitation in the target text (TT of semantic relations which can be deduced from the ST by means of inferences.Neste artigo, discute-se a transferência de relações semânticas entre proposições com base em um estudo piloto com objetivos didáticos realizado na Copenhagen Business School. As relações analisadas eram não marcadas no texto de partida (TP. Procura-se investigar até que ponto a tradução da coesão textual é objeto de processamento mental por tradutores quase profissionais durante o processo de tradução e até que ponto os tradutores quase profissionais optam por uma estratégia envolvendo explicitação no texto de chegada (TC das relações semânticas que podem ser deduzidas a partir do TP através de inferências.

  10. The Processing of Causal and Hierarchical Relations in Semantic Memory as Revealed by N400 and Frontal Negativity.

    Directory of Open Access Journals (Sweden)

    Xiuling Liang

    Full Text Available Most current studies investigating semantic memory have focused on associative (ring-emerald or taxonomic relations (bird-sparrow. Little is known about the question of how causal relations (virus-epidemic are stored and accessed in semantic memory. The goal of this study was to examine the processing of causally related, general associatively related and hierarchically related word pairs when participants were required to evaluate whether pairs of words were related in any way. The ERP data showed that the N400 amplitude (200-500 ms elicited by unrelated related words was more negative than all related words. Furthermore, the late frontal distributed negativity (500-700 ms elicited by causally related words was smaller than hierarchically related words, but not for general associated words. These results suggested the processing of causal relations and hierarchical relations in semantic memory recruited different degrees of cognitive resources, especially for role binding.

  11. Varieties of semantic ‘access’ deficit in Wernicke’s aphasia and semantic aphasia

    Science.gov (United States)

    Robson, Holly; Lambon Ralph, Matthew A.; Jefferies, Elizabeth

    2015-01-01

    Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke’s aphasia, associated with poor auditory–verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic ‘access’ deficit, as opposed to the ‘storage’ deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of ‘access’ impairment—related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke’s aphasia). We used a case series design to compare patients with Wernicke’s aphasia and those with semantic aphasia on Warrington’s paradigmatic assessment of semantic ‘access’ deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic ‘blocking’ effects). Patients with Wernicke’s aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability—one that mapped onto classical ‘syndromes’ and one that did not—predicted aspects of the semantic ‘access’ deficit. Both semantic aphasia and Wernicke’s aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke’s aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially

  12. Interactions between mood and the structure of semantic memory: event-related potentials evidence.

    Science.gov (United States)

    Pinheiro, Ana P; del Re, Elisabetta; Nestor, Paul G; McCarley, Robert W; Gonçalves, Óscar F; Niznikiewicz, Margaret

    2013-06-01

    Recent evidence suggests that affect acts as modulator of cognitive processes and in particular that induced mood has an effect on the way semantic memory is used on-line. We used event-related potentials (ERPs) to examine affective modulation of semantic information processing under three different moods: neutral, positive and negative. Fifteen subjects read 324 pairs of sentences, after mood induction procedure with 30 pictures of neutral, 30 pictures of positive and 30 pictures of neutral valence: 108 sentences were read in each mood induction condition. Sentences ended with three word types: expected words, within-category violations, and between-category violations. N400 amplitude was measured to the three word types under each mood induction condition. Under neutral mood, a congruency (more negative N400 amplitude for unexpected relative to expected endings) and a category effect (more negative N400 amplitude for between- than to within-category violations) were observed. Also, results showed differences in N400 amplitude for both within- and between-category violations as a function of mood: while positive mood tended to facilitate the integration of unexpected but related items, negative mood made their integration as difficult as unexpected and unrelated items. These findings suggest the differential impact of mood on access to long-term semantic memory during sentence comprehension.

  13. Interpreting semantic clustering effects in free recall.

    Science.gov (United States)

    Manning, Jeremy R; Kahana, Michael J

    2012-07-01

    The order in which participants choose to recall words from a studied list of randomly selected words provides insights into how memories of the words are represented, organised, and retrieved. One pervasive finding is that when a pair of semantically related words (e.g., "cat" and "dog") is embedded in the studied list, the related words are often recalled successively. This tendency to successively recall semantically related words is termed semantic clustering (Bousfield, 1953; Bousfield & Sedgewick, 1944; Cofer, Bruce, & Reicher, 1966). Measuring semantic clustering effects requires making assumptions about which words participants consider to be similar in meaning. However, it is often difficult to gain insights into individual participants' internal semantic models, and for this reason researchers typically rely on standardised semantic similarity metrics. Here we use simulations to gain insights into the expected magnitudes of semantic clustering effects given systematic differences between participants' internal similarity models and the similarity metric used to quantify the degree of semantic clustering. Our results provide a number of useful insights into the interpretation of semantic clustering effects in free recall.

  14. Why all the confusion? Experimental task explains discrepant semantic priming effects in schizophrenia under “automatic” conditions: evidence from Event-Related Potentials

    OpenAIRE

    Kreher, Donna A.; Goff, Donald; Kuperberg, Gina R.

    2009-01-01

    The schizophrenia research literature contains many differing accounts of semantic memory function in schizophrenia as assessed through the semantic priming paradigm. Most recently, Event-Related Potentials (ERPs) have been used to demonstrate both increased and decreased semantic priming at a neural level in schizophrenia patients, relative to healthy controls. The present study used ERPs to investigate the role of behavioral task in determining neural semantic priming effects in schizophren...

  15. Connecting Archaeological Data and Grey Literature via Semantic Cross Search

    Directory of Open Access Journals (Sweden)

    Douglas Tudhope

    2011-07-01

    Full Text Available Differing terminology and database structure hinders meaningful cross search of excavation datasets. Matching free text grey literature reports with datasets poses yet more challenges. Conventional search techniques are unable to cross search between archaeological datasets and Web-based grey literature. Results are reported from two AHRC funded research projects that investigated the use of semantic techniques to link digital archive databases, vocabularies and associated grey literature. STAR (Semantic Technologies for Archaeological Resources was a collaboration between the University of Glamorgan, Hypermedia Research Unit and English Heritage (EH. The main outcome is a research Demonstrator (available online, which cross searches over excavation datasets from different database schemas, including Raunds Roman, Raunds Prehistoric, Museum of London, Silchester Roman and Stanwick sampling. The system additionally cross searches over an extract of excavation reports from the OASIS index of grey literature, operated by the Archaeology Data Service (ADS. A conceptual framework provided by the CIDOC Conceptual Reference Model (CRM integrates the different database structures and the metadata automatically generated from the OASIS reports by natural language processing techniques. The methods employed for extracting semantic RDF representations from the datasets and the information extraction from grey literature are described. The STELLAR project provides freely available tools to reduce the costs of mapping and extracting data to semantic search systems such as the Demonstrator and to linked data representation generally. Detailed use scenarios (and a screen capture video provide a basis for a discussion of key issues, including cost-benefits, ontology modelling, mapping, terminology control, semantic implementation and information extraction issues. The scenarios show that semantic interoperability can be achieved by mapping and extracting

  16. Psychologizing the Semantics of Fiction

    Directory of Open Access Journals (Sweden)

    John Woods

    2010-04-01

    Full Text Available Psychologiser la sémantique de la fictionLes théoriciens sémantistes de la fiction cherchent typiquement à expliquer nos relations sémantiques au fictionnel dans le contexte plus général des théories de la référence, privilégiant une explication de la sémantique sur le psychologique. Dans cet article, nous défendons une dépendance inverse. Par l’éclaircissement de nos relations psychologiques au fictionnel, nous trouverons un guide pour savoir comment développer une sémantique de la fiction. S’ensuivra une esquisse de la sémantique.Semantic theorists of fiction typically look for an account of our semantic relations to the fictional within general-purpose theories of reference, privileging an explanation of the semantic over the psychological. In this paper, we counsel a reverse dependency. In sorting out our psychological relations to the fictional, there is useful guidance about how to proceed with the semantics of fiction. A sketch of the semantics follows.

  17. Applied Semantic Web Technologies

    CERN Document Server

    Sugumaran, Vijayan

    2011-01-01

    The rapid advancement of semantic web technologies, along with the fact that they are at various levels of maturity, has left many practitioners confused about the current state of these technologies. Focusing on the most mature technologies, Applied Semantic Web Technologies integrates theory with case studies to illustrate the history, current state, and future direction of the semantic web. It maintains an emphasis on real-world applications and examines the technical and practical issues related to the use of semantic technologies in intelligent information management. The book starts with

  18. Semantic Annotation of Unstructured Documents Using Concepts Similarity

    Directory of Open Access Journals (Sweden)

    Fernando Pech

    2017-01-01

    Full Text Available There is a large amount of information in the form of unstructured documents which pose challenges in the information storage, search, and retrieval. This situation has given rise to several information search approaches. Some proposals take into account the contextual meaning of the terms specified in the query. Semantic annotation technique can help to retrieve and extract information in unstructured documents. We propose a semantic annotation strategy for unstructured documents as part of a semantic search engine. In this proposal, ontologies are used to determine the context of the entities specified in the query. Our strategy for extracting the context is focused on concepts similarity. Each relevant term of the document is associated with an instance in the ontology. The similarity between each of the explicit relationships is measured through the combination of two types of associations: the association between each pair of concepts and the calculation of the weight of the relationships.

  19. Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction.

    Directory of Open Access Journals (Sweden)

    Zude Zhu

    Full Text Available While aging is associated with increased knowledge, it is also associated with decreased semantic integration. To investigate brain activation changes during semantic integration, a sample of forty-eight 25-75 year-old adults read sentences with high cloze (HC and low cloze (LC probability while functional magnetic resonance imaging was conducted. Significant age-related reduction of cloze effect (LC vs. HC was found in several regions, especially the left middle frontal gyrus (MFG and right inferior frontal gyrus (IFG, which play an important role in semantic integration. Moreover, when accounting for global gray matter volume reduction, the age-cloze correlation in the left MFG and right IFG was absent. The results suggest that brain structural atrophy may disrupt brain response in aging brains, which then show less brain engagement in semantic integration.

  20. Computer-Assisted Program Reasoning Based on a Relational Semantics of Programs

    Directory of Open Access Journals (Sweden)

    Wolfgang Schreiner

    2012-02-01

    Full Text Available We present an approach to program reasoning which inserts between a program and its verification conditions an additional layer, the denotation of the program expressed in a declarative form. The program is first translated into its denotation from which subsequently the verification conditions are generated. However, even before (and independently of any verification attempt, one may investigate the denotation itself to get insight into the "semantic essence" of the program, in particular to see whether the denotation indeed gives reason to believe that the program has the expected behavior. Errors in the program and in the meta-information may thus be detected and fixed prior to actually performing the formal verification. More concretely, following the relational approach to program semantics, we model the effect of a program as a binary relation on program states. A formal calculus is devised to derive from a program a logic formula that describes this relation and is subject for inspection and manipulation. We have implemented this idea in a comprehensive form in the RISC ProgramExplorer, a new program reasoning environment for educational purposes which encompasses the previously developed RISC ProofNavigator as an interactive proving assistant.

  1. A Method of Extracting Ontology Module Using Concept Relations for Sharing Knowledge in Mobile Cloud Computing Environment

    Directory of Open Access Journals (Sweden)

    Keonsoo Lee

    2014-01-01

    Full Text Available In mobile cloud computing environment, the cooperation of distributed computing objects is one of the most important requirements for providing successful cloud services. To satisfy this requirement, all the members, who are employed in the cooperation group, need to share the knowledge for mutual understanding. Even if ontology can be the right tool for this goal, there are several issues to make a right ontology. As the cost and complexity of managing knowledge increase according to the scale of the knowledge, reducing the size of ontology is one of the critical issues. In this paper, we propose a method of extracting ontology module to increase the utility of knowledge. For the given signature, this method extracts the ontology module, which is semantically self-contained to fulfill the needs of the service, by considering the syntactic structure and semantic relation of concepts. By employing this module, instead of the original ontology, the cooperation of computing objects can be performed with less computing load and complexity. In particular, when multiple external ontologies need to be combined for more complex services, this method can be used to optimize the size of shared knowledge.

  2. A method of extracting ontology module using concept relations for sharing knowledge in mobile cloud computing environment.

    Science.gov (United States)

    Lee, Keonsoo; Rho, Seungmin; Lee, Seok-Won

    2014-01-01

    In mobile cloud computing environment, the cooperation of distributed computing objects is one of the most important requirements for providing successful cloud services. To satisfy this requirement, all the members, who are employed in the cooperation group, need to share the knowledge for mutual understanding. Even if ontology can be the right tool for this goal, there are several issues to make a right ontology. As the cost and complexity of managing knowledge increase according to the scale of the knowledge, reducing the size of ontology is one of the critical issues. In this paper, we propose a method of extracting ontology module to increase the utility of knowledge. For the given signature, this method extracts the ontology module, which is semantically self-contained to fulfill the needs of the service, by considering the syntactic structure and semantic relation of concepts. By employing this module, instead of the original ontology, the cooperation of computing objects can be performed with less computing load and complexity. In particular, when multiple external ontologies need to be combined for more complex services, this method can be used to optimize the size of shared knowledge.

  3. Fuzzy concept analysis for semantic knowledge extraction

    OpenAIRE

    De Maio, Carmen

    2012-01-01

    2010 - 2011 Availability of controlled vocabularies, ontologies, and so on is enabling feature to provide some added values in terms of knowledge management. Nevertheless, the design, maintenance and construction of domain ontologies are a human intensive and time consuming task. The Knowledge Extraction consists of automatic techniques aimed to identify and to define relevant concepts and relations of the domain of interest by analyzing structured (relational databases, XML) and unstructu...

  4. Reactive Kripke semantics

    CERN Document Server

    Gabbay, Dov M

    2013-01-01

    This text offers an extension to the traditional Kripke semantics for non-classical logics by adding the notion of reactivity. Reactive Kripke models change their accessibility relation as we progress in the evaluation process of formulas in the model. This feature makes the reactive Kripke semantics strictly stronger and more applicable than the traditional one. Here we investigate the properties and axiomatisations of this new and most effective semantics, and we offer a wide landscape of applications of the idea of reactivity. Applied topics include reactive automata, reactive grammars, rea

  5. Neural differentiation of lexico-syntactic categories or semantic features? event-related potential evidence for both.

    Science.gov (United States)

    Kellenbach, Marion L; Wijers, Albertus A; Hovius, Marjolijn; Mulder, Juul; Mulder, Gijsbertus

    2002-05-15

    Event-related potentials (ERPs) were used to investigate whether processing differences between nouns and verbs can be accounted for by the differential salience of visual-perceptual and motor attributes in their semantic specifications. Three subclasses of nouns and verbs were selected, which differed in their semantic attribute composition (abstract, high visual, high visual and motor). Single visual word presentation with a recognition memory task was used. While multiple robust and parallel ERP effects were observed for both grammatical class and attribute type, there were no interactions between these. This pattern of effects provides support for lexical-semantic knowledge being organized in a manner that takes account both of category-based (grammatical class) and attribute-based distinctions.

  6. Productive extension of semantic memory in school-aged children: Relations with reading comprehension and deployment of cognitive resources.

    Science.gov (United States)

    Bauer, Patricia J; Blue, Shala N; Xu, Aoxiang; Esposito, Alena G

    2016-07-01

    We investigated 7- to 10-year-old children's productive extension of semantic memory through self-generation of new factual knowledge derived through integration of separate yet related facts learned through instruction or through reading. In Experiment 1, an experimenter read the to-be-integrated facts. Children successfully learned and integrated the information and used it to further extend their semantic knowledge, as evidenced by high levels of correct responses in open-ended and forced-choice testing. In Experiment 2, on half of the trials, the to-be-integrated facts were read by an experimenter (as in Experiment 1) and on half of the trials, children read the facts themselves. Self-generation performance was high in both conditions (experimenter- and self-read); in both conditions, self-generation of new semantic knowledge was related to an independent measure of children's reading comprehension. In Experiment 3, the way children deployed cognitive resources during reading was predictive of their subsequent recall of newly learned information derived through integration. These findings indicate self-generation of new semantic knowledge through integration in school-age children as well as relations between this productive means of extension of semantic memory and cognitive processes engaged during reading. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  7. Learning Document Semantic Representation with Hybrid Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Yan Yan

    2015-01-01

    it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance.

  8. Snapshots for Semantic Maps

    National Research Council Canada - National Science Library

    Nielsen, Curtis W; Ricks, Bob; Goodrich, Michael A; Bruemmer, David; Few, Doug; Walton, Miles

    2004-01-01

    .... Semantic maps are a relatively new approach to information presentation. Semantic maps provide more detail about an environment than typical maps because they are augmented by icons or symbols that provide meaning for places or objects of interest...

  9. Higher Language Ability is Related to Angular Gyrus Activation Increase During Semantic Processing, Independent of Sentence Incongruency

    Science.gov (United States)

    Van Ettinger-Veenstra, Helene; McAllister, Anita; Lundberg, Peter; Karlsson, Thomas; Engström, Maria

    2016-01-01

    This study investigates the relation between individual language ability and neural semantic processing abilities. Our aim was to explore whether high-level language ability would correlate to decreased activation in language-specific regions or rather increased activation in supporting language regions during processing of sentences. Moreover, we were interested if observed neural activation patterns are modulated by semantic incongruency similarly to previously observed changes upon syntactic congruency modulation. We investigated 27 healthy adults with a sentence reading task—which tapped language comprehension and inference, and modulated sentence congruency—employing functional magnetic resonance imaging (fMRI). We assessed the relation between neural activation, congruency modulation, and test performance on a high-level language ability assessment with multiple regression analysis. Our results showed increased activation in the left-hemispheric angular gyrus extending to the temporal lobe related to high language ability. This effect was independent of semantic congruency, and no significant relation between language ability and incongruency modulation was observed. Furthermore, there was a significant increase of activation in the inferior frontal gyrus (IFG) bilaterally when the sentences were incongruent, indicating that processing incongruent sentences was more demanding than processing congruent sentences and required increased activation in language regions. The correlation of high-level language ability with increased rather than decreased activation in the left angular gyrus, a region specific for language processing, is opposed to what the neural efficiency hypothesis would predict. We can conclude that no evidence is found for an interaction between semantic congruency related brain activation and high-level language performance, even though the semantic incongruent condition shows to be more demanding and evoking more neural activation. PMID

  10. Higher language ability is related to angular gyrus activation increase during semantic processing, independent of sentence incongruency

    Directory of Open Access Journals (Sweden)

    Helene eVan Ettinger-Veenstra

    2016-03-01

    Full Text Available This study investigates the relation between individual language ability and neural semantic processing abilities. Our aim was to explore whether high-level language ability would correlate to decreased activation in language-specific regions or rather increased activation in supporting language regions during processing of sentences. Moreover, we were interested if observed neural activation patterns are modulated by semantic incongruency similarly to previously observed changes upon syntactic congruency modulation. We investigated 27 healthy adults with a sentence reading task - which tapped language comprehension and inference, and modulated sentence congruency - employing functional magnetic resonance imaging. We assessed the relation between neural activation, congruency modulation, and test performance on a high-level language ability assessment with multiple regression analysis. Our results showed increased activation in the left-hemispheric angular gyrus extending to the temporal lobe related to high language ability. This effect was independent of semantic congruency, and no significant relation between language ability and incongruency modulation was observed. Furthermore, a significant increase of activation in the inferior frontal gyrus bilaterally when the sentences were incongruent, indicating that processing incongruent sentences was more demanding than processing congruent sentences and required increased activation in language regions. The correlation of high-level language ability with increased rather than decreased activation in the left angular gyrus, a region specific for language processing is opposed to what the neural efficiency hypothesis would predict. We can conclude that there is no evidence found for an interaction between semantic congruency related brain activation and high-level language performance, even though the semantic incongruent condition shows to be more demanding and evoking more neural activation.

  11. Motivated encoding selectively promotes memory for future inconsequential semantically-related events.

    Science.gov (United States)

    Oyarzún, Javiera P; Packard, Pau A; de Diego-Balaguer, Ruth; Fuentemilla, Lluis

    2016-09-01

    Neurobiological models of long-term memory explain how memory for inconsequential events fades, unless these happen before or after other relevant (i.e., rewarding or aversive) or novel events. Recently, it has been shown in humans that retrospective and prospective memories are selectively enhanced if semantically related events are paired with aversive stimuli. However, it remains unclear whether motivating stimuli, as opposed to aversive, have the same effect in humans. Here, participants performed a three phase incidental encoding task where one semantic category was rewarded during the second phase. A memory test 24h after, but not immediately after encoding, revealed that memory for inconsequential items was selectively enhanced only if items from the same category had been previously, but not subsequently, paired with rewards. This result suggests that prospective memory enhancement of reward-related information requires, like previously reported for aversive memories, of a period of memory consolidation. The current findings provide the first empirical evidence in humans that the effects of motivated encoding are selectively and prospectively prolonged over time. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Neural correlates of relational memory: successful encoding and retrieval of semantic and perceptual associations

    NARCIS (Netherlands)

    Prince, S.E.; Daselaar, S.M.; Cabeza, R.

    2005-01-01

    Using event-related functional magnetic resonance imaging, we identified brain regions involved in successful relational memory (RM) during encoding and retrieval for semantic and perceptual associations or in general, independent of phase and content. Participants were scanned while encoding and

  13. The Impact of Presenting Semantically Related Clusters of New Words on Iranian Intermediate EFL learners' Vocabulary Acquisition

    Directory of Open Access Journals (Sweden)

    Saiede Shiri

    2017-09-01

    Full Text Available Teaching vocabulary in semantically related sets use as a common practice by EFL teachers. The present study tests the effectiveness of this techniques by comparing it with semantically unrelated clusters as the other technique on Iranian intermediate EFL learners. In the study three intact classes of participants studying at Isfahan were presented with a set of unrelated words through “ 504 Absolutely Essential words”, a set of related words through “The Oxford Picture Dictionary “, and the control group were presented some new words through six texts from “Reading Through Interaction”. Comparing of the results indicated that, while both techniques help the learners to acquire new sets of the words, presenting words in semantically unrelated sets seems to be more effective.

  14. High Performance Descriptive Semantic Analysis of Semantic Graph Databases

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Adolf, Robert D.; al-Saffar, Sinan; Feo, John T.; Haglin, David J.; Mackey, Greg E.; Mizell, David W.

    2011-06-02

    As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to understand their inherent semantic structure, whether codified in explicit ontologies or not. Our group is researching novel methods for what we call descriptive semantic analysis of RDF triplestores, to serve purposes of analysis, interpretation, visualization, and optimization. But data size and computational complexity makes it increasingly necessary to bring high performance computational resources to bear on this task. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multi-threaded architecture of the Cray XMT platform, conventional servers, and large data stores. In this paper we describe that architecture and our methods, and present the results of our analyses of basic properties, connected components, namespace interaction, and typed paths such for the Billion Triple Challenge 2010 dataset.

  15. [Semantic Network Analysis of Online News and Social Media Text Related to Comprehensive Nursing Care Service].

    Science.gov (United States)

    Kim, Minji; Choi, Mona; Youm, Yoosik

    2017-12-01

    As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies. © 2017 Korean Society of Nursing Science

  16. Semantic ambiguity processing in sentence context: Evidence from event-related fMRI

    NARCIS (Netherlands)

    Zempleni, Monika-Zita; Renken, Remco; Hoeks, John C. J.; Hoogduin, Johannes M.; Stowe, Laurie A.

    2007-01-01

    Lexical semantic ambiguity is the phenomenon when a word has multiple meanings (e.g. 'bank'). The aim of this event-related functional MRI study was to identify those brain areas, which are involved in contextually driven ambiguity resolution. Ambiguous words were selected which have a most

  17. Event-related potentials to event-related words: grammatical class and semantic attributes in the representation of knowledge.

    Science.gov (United States)

    Barber, Horacio A; Kousta, Stavroula-Thaleia; Otten, Leun J; Vigliocco, Gabriella

    2010-05-21

    A number of recent studies have provided contradictory evidence on the question of whether grammatical class plays a role in the neural representation of lexical knowledge. Most of the previous studies comparing the processing of nouns and verbs, however, confounded word meaning and grammatical class by comparing verbs referring to actions with nouns referring to objects. Here, we recorded electrical brain activity from native Italian speakers reading single words all referring to events (e.g., corsa [the run]; correre [to run]), thus avoiding confounding nouns and verbs with objects and actions. We manipulated grammatical class (noun versus verb) as well as semantic attributes (motor versus sensory events). Activity between 300 and 450ms was more negative for nouns than verbs, and for sensory than motor words, over posterior scalp sites. These grammatical class and semantic effects were not dissociable in terms of latency, duration, or scalp distribution. In a later time window (450-110ms) and at frontal regions, grammatical class and semantic effects interacted; motor verbs were more positive than the other three word categories. We suggest that the lack of a temporal and topographical dissociation between grammatical class and semantic effects in the time range of the N400 component is compatible with an account in which both effects reflect the same underlying process related to meaning retrieval, and we link the later effect with working memory operations associated to the experimental task. Copyright 2010 Elsevier B.V. All rights reserved.

  18. Adventures in semantic publishing: exemplar semantic enhancements of a research article.

    Directory of Open Access Journals (Sweden)

    David Shotton

    2009-04-01

    Full Text Available Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit "Citations in Context", and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/. The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own

  19. Populating the Semantic Web by Macro-reading Internet Text

    Science.gov (United States)

    Mitchell, Tom M.; Betteridge, Justin; Carlson, Andrew; Hruschka, Estevam; Wang, Richard

    A key question regarding the future of the semantic web is "how will we acquire structured information to populate the semantic web on a vast scale?" One approach is to enter this information manually. A second approach is to take advantage of pre-existing databases, and to develop common ontologies, publishing standards, and reward systems to make this data widely accessible. We consider here a third approach: developing software that automatically extracts structured information from unstructured text present on the web. We also describe preliminary results demonstrating that machine learning algorithms can learn to extract tens of thousands of facts to populate a diverse ontology, with imperfect but reasonably good accuracy.

  20. Semantic Preview Benefit during Reading

    Science.gov (United States)

    Hohenstein, Sven; Kliegl, Reinhold

    2014-01-01

    Word features in parafoveal vision influence eye movements during reading. The question of whether readers extract semantic information from parafoveal words was studied in 3 experiments by using a gaze-contingent display change technique. Subjects read German sentences containing 1 of several preview words that were replaced by a target word…

  1. Priming the semantic neighbourhood during the attentional blink.

    Directory of Open Access Journals (Sweden)

    Irina M Harris

    2010-09-01

    Full Text Available When two targets are presented in close temporal proximity amongst a rapid serial visual stream of distractors, a period of disrupted attention and attenuated awareness lasting 200-500 ms follows identification of the first target (T1. This phenomenon is known as the "attentional blink" (AB and is generally attributed to a failure to consolidate information in visual short-term memory due to depleted or disrupted attentional resources. Previous research has shown that items presented during the AB that fail to reach conscious awareness are still processed to relatively high levels, including the level of meaning. For example, missed word stimuli have been shown to prime later targets that are closely associated words. Although these findings have been interpreted as evidence for semantic processing during the AB, closely associated words (e.g., day-night may also rely on specific, well-worn, lexical associative links which enhance attention to the relevant target.We used a measure of semantic distance to create prime-target pairs that are conceptually close, but have low word associations (e.g., wagon and van and investigated priming from a distractor stimulus presented during the AB to a subsequent target (T2. The stimuli were words (concrete nouns in Experiment 1 and the corresponding pictures of objects in Experiment 2. In both experiments, report of T2 was facilitated when this item was preceded by a semantically-related distractor.This study is the first to show conclusively that conceptual information is extracted from distractor stimuli presented during a period of attenuated awareness and that this information spreads to neighbouring concepts within a semantic network.

  2. Testing the limits of the semantic illusion phenomenon: ERPs reveal temporary semantic change deafness in discourse comprehension

    NARCIS (Netherlands)

    Nieuwland, M.S.; van Berkum, J.J.A.

    2005-01-01

    In general, language comprehension is surprisingly reliable. Listeners very rapidly extract meaning from the unfolding speech signal, on a word-by-word basis, and usually successfully. Research on ‘semantic illusions’ however suggests that under certain conditions, people fail to notice that the

  3. Asymmetries in gender-related familiarity with different semantic categories. Data from normal adults.

    Science.gov (United States)

    Gainotti, Guido; Spinelli, Pietro; Scaricamazza, Eugenia; Marra, Camillo

    2013-01-01

    The mechanisms subsuming the brain organization of categories and the corresponding gender related asymmetries are controversial. Some authors believe that the brain organization of categories is innate, whereas other authors maintain that it is shaped by experience. According to these interpretations, gender-related asymmetries should respectively be inborn or result from the influence of social roles. In a previous study, assessing the familiarity of young students with different 'biological' and 'artefact' categories, we had observed no gender-related difference on any of these categories. Since these data could be due to the fact that our students belonged to a generation in which the traditional social roles have almost completely disappeared, we predicted that gender-related asymmetries should be found in older men and women. The familiarity of young and elderly men and women with various semantic categories was, therefore, studied presenting in the verbal and pictorial modality different kinds of living and artefact categories. Results confirmed the hypothesis, because elderly women showed a greater familiarity for flowers and elderly men for animals. These findings are consistent with the hypothesis assuming that gender-related asymmetries for different semantic categories is due to the influence of gender-related social roles.

  4. Topics in Semantics-based Program Manipulation

    DEFF Research Database (Denmark)

    Grobauer, Bernt

    four articles in the field of semantics-based techniques for program manipulation: three articles are about partial evaluation, a method for program specialization; the fourth article treats an approach to automatic cost analysis. Partial evaluation optimizes programs by specializing them with respect...... article in this dissertation describes how the second Futamura projection can be achieved for type-directed partial evaluation (TDPE), a relatively recent approach to partial evaluation: We derive an ML implementation of the second Futamura projection for TDPE. Due to the differences between ‘traditional...... denotational semantics—allows us to relate various possible semantics to each other both conceptually and formally. We thus are able to explain goal-directed evaluation using an intuitive list-based semantics, while using a continuation semantics for semantics-based compilation through partial evaluation...

  5. The construction of semantic memory: grammar based representations learned from relational episodic information

    Directory of Open Access Journals (Sweden)

    Francesco P Battaglia

    2011-08-01

    Full Text Available After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation, collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the inside-outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of ``sleep replay'' of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata.

  6. The Construction of Semantic Memory: Grammar-Based Representations Learned from Relational Episodic Information

    Science.gov (United States)

    Battaglia, Francesco P.; Pennartz, Cyriel M. A.

    2011-01-01

    After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation), collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the inside–outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of “sleep replay” of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata. PMID:21887143

  7. Semantic Blogging : Spreading the Semantic Web Meme

    OpenAIRE

    Cayzer, Steve

    2004-01-01

    This paper is about semantic blogging, an application of the semantic web to blogging. The semantic web promises to make the web more useful by endowing metadata with machine processable semantics. Blogging is a lightweight web publishing paradigm which provides a very low barrier to entry, useful syndication and aggregation behaviour, a simple to understand structure and decentralized construction of a rich information network. Semantic blogging builds upon the success and clear network valu...

  8. Verbal and non-verbal semantic impairment: From fluent primary progressive aphasia to semantic dementia

    Directory of Open Access Journals (Sweden)

    Mirna Lie Hosogi Senaha

    Full Text Available Abstract Selective disturbances of semantic memory have attracted the interest of many investigators and the question of the existence of single or multiple semantic systems remains a very controversial theme in the literature. Objectives: To discuss the question of multiple semantic systems based on a longitudinal study of a patient who presented semantic dementia from fluent primary progressive aphasia. Methods: A 66 year-old woman with selective impairment of semantic memory was examined on two occasions, undergoing neuropsychological and language evaluations, the results of which were compared to those of three paired control individuals. Results: In the first evaluation, physical examination was normal and the score on the Mini-Mental State Examination was 26. Language evaluation revealed fluent speech, anomia, disturbance in word comprehension, preservation of the syntactic and phonological aspects of the language, besides surface dyslexia and dysgraphia. Autobiographical and episodic memories were relatively preserved. In semantic memory tests, the following dissociation was found: disturbance of verbal semantic memory with preservation of non-verbal semantic memory. Magnetic resonance of the brain revealed marked atrophy of the left anterior temporal lobe. After 14 months, the difficulties in verbal semantic memory had become more severe and the semantic disturbance, limited initially to the linguistic sphere, had worsened to involve non-verbal domains. Conclusions: Given the dissociation found in the first examination, we believe there is sufficient clinical evidence to refute the existence of a unitary semantic system.

  9. Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

    Science.gov (United States)

    Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

    2010-01-01

    Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/. 2009 Elsevier B.V. All rights reserved.

  10. To predict or not to predict: influences of task and strategy on the processing of semantic relations.

    Science.gov (United States)

    Roehm, Dietmar; Bornkessel-Schlesewsky, Ina; Rösler, Frank; Schlesewsky, Matthias

    2007-08-01

    We report a series of event-related potential experiments designed to dissociate the functionally distinct processes involved in the comprehension of highly restricted lexical-semantic relations (antonyms). We sought to differentiate between influences of semantic relatedness (which are independent of the experimental setting) and processes related to predictability (which differ as a function of the experimental environment). To this end, we conducted three ERP studies contrasting the processing of antonym relations (black-white) with that of related (black-yellow) and unrelated (black-nice) word pairs. Whereas the lexical-semantic manipulation was kept constant across experiments, the experimental environment and the task demands varied: Experiment 1 presented the word pairs in a sentence context of the form The opposite of X is Y and used a sensicality judgment. Experiment 2 used a word pair presentation mode and a lexical decision task. Experiment 3 also examined word pairs, but with an antonymy judgment task. All three experiments revealed a graded N400 response (unrelated > related > antonyms), thus supporting the assumption that semantic associations are processed automatically. In addition, the experiments revealed that, in highly constrained task environments, the N400 gradation occurs simultaneously with a P300 effect for the antonym condition, thus leading to the superficial impression of an extremely "reduced" N400 for antonym pairs. Comparisons across experiments and participant groups revealed that the P300 effect is not only a function of stimulus constraints (i.e., sentence context) and experimental task, but that it is also crucially influenced by individual processing strategies used to achieve successful task performance.

  11. Biomedical semantics in the Semantic Web.

    Science.gov (United States)

    Splendiani, Andrea; Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott

    2011-03-07

    The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.

  12. Automatic extraction of legal concepts and definitions

    NARCIS (Netherlands)

    Winkels, R.; Hoekstra, R.

    2012-01-01

    In this paper we present the results of an experiment in automatic concept and definition extraction from written sources of law using relatively simple natural language and standard semantic web technology. The software was tested on six laws from the tax domain.

  13. Mining Significant Semantic Locations from GPS Data

    DEFF Research Database (Denmark)

    Cao, Xin; Cong, Gao; Jensen, Christian Søndergaard

    2010-01-01

    With the increasing deployment and use of GPS-enabled devices, massive amounts of GPS data are becoming available. We propose a general framework for the mining of semantically meaningful, significant locations, e.g., shopping malls and restaurants, from such data. We present techniques capable...... of extracting semantic locations from GPS data. We capture the relationships between locations and between locations and users with a graph. Significance is then assigned to locations using random walks over the graph that propagates significance among the locations. In doing so, mutual reinforcement between...

  14. Mining significant semantic locations from GPS data

    DEFF Research Database (Denmark)

    Cao, Xin; Cong, Gao; Jensen, Christian S.

    2010-01-01

    With the increasing deployment and use of GPS-enabled devices, massive amounts of GPS data are becoming available. We propose a general framework for the mining of semantically meaningful, significant locations, e.g., shopping malls and restaurants, from such data. We present techniques capable...... of extracting semantic locations from GPS data. We capture the relationships between locations and between locations and users with a graph. Significance is then assigned to locations using random walks over the graph that propagates significance among the locations. In doing so, mutual reinforcement between...

  15. Semantic role labeling for protein transport predicates

    Directory of Open Access Journals (Sweden)

    Martin James H

    2008-06-01

    Full Text Available Abstract Background Automatic semantic role labeling (SRL is a natural language processing (NLP technique that maps sentences to semantic representations. This technique has been widely studied in the recent years, but mostly with data in newswire domains. Here, we report on a SRL model for identifying the semantic roles of biomedical predicates describing protein transport in GeneRIFs – manually curated sentences focusing on gene functions. To avoid the computational cost of syntactic parsing, and because the boundaries of our protein transport roles often did not match up with syntactic phrase boundaries, we approached this problem with a word-chunking paradigm and trained support vector machine classifiers to classify words as being at the beginning, inside or outside of a protein transport role. Results We collected a set of 837 GeneRIFs describing movements of proteins between cellular components, whose predicates were annotated for the semantic roles AGENT, PATIENT, ORIGIN and DESTINATION. We trained these models with the features of previous word-chunking models, features adapted from phrase-chunking models, and features derived from an analysis of our data. Our models were able to label protein transport semantic roles with 87.6% precision and 79.0% recall when using manually annotated protein boundaries, and 87.0% precision and 74.5% recall when using automatically identified ones. Conclusion We successfully adapted the word-chunking classification paradigm to semantic role labeling, applying it to a new domain with predicates completely absent from any previous studies. By combining the traditional word and phrasal role labeling features with biomedical features like protein boundaries and MEDPOST part of speech tags, we were able to address the challenges posed by the new domain data and subsequently build robust models that achieved F-measures as high as 83.1. This system for extracting protein transport information from Gene

  16. SAS- Semantic Annotation Service for Geoscience resources on the web

    Science.gov (United States)

    Elag, M.; Kumar, P.; Marini, L.; Li, R.; Jiang, P.

    2015-12-01

    There is a growing need for increased integration across the data and model resources that are disseminated on the web to advance their reuse across different earth science applications. Meaningful reuse of resources requires semantic metadata to realize the semantic web vision for allowing pragmatic linkage and integration among resources. Semantic metadata associates standard metadata with resources to turn them into semantically-enabled resources on the web. However, the lack of a common standardized metadata framework as well as the uncoordinated use of metadata fields across different geo-information systems, has led to a situation in which standards and related Standard Names abound. To address this need, we have designed SAS to provide a bridge between the core ontologies required to annotate resources and information systems in order to enable queries and analysis over annotation from a single environment (web). SAS is one of the services that are provided by the Geosematnic framework, which is a decentralized semantic framework to support the integration between models and data and allow semantically heterogeneous to interact with minimum human intervention. Here we present the design of SAS and demonstrate its application for annotating data and models. First we describe how predicates and their attributes are extracted from standards and ingested in the knowledge-base of the Geosemantic framework. Then we illustrate the application of SAS in annotating data managed by SEAD and annotating simulation models that have web interface. SAS is a step in a broader approach to raise the quality of geoscience data and models that are published on the web and allow users to better search, access, and use of the existing resources based on standard vocabularies that are encoded and published using semantic technologies.

  17. Workspaces in the Semantic Web

    Science.gov (United States)

    Wolfe, Shawn R.; Keller, RIchard M.

    2005-01-01

    Due to the recency and relatively limited adoption of Semantic Web technologies. practical issues related to technology scaling have received less attention than foundational issues. Nonetheless, these issues must be addressed if the Semantic Web is to realize its full potential. In particular, we concentrate on the lack of scoping methods that reduce the size of semantic information spaces so they are more efficient to work with and more relevant to an agent's needs. We provide some intuition to motivate the need for such reduced information spaces, called workspaces, give a formal definition, and suggest possible methods of deriving them.

  18. Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction

    OpenAIRE

    Zhu, Zude; Yang, Fengjun; Li, Dongning; Zhou, Lianjun; Liu, Ying; Zhang, Ying; Chen, Xuezhi

    2017-01-01

    While aging is associated with increased knowledge, it is also associated with decreased semantic integration. To investigate brain activation changes during semantic integration, a sample of forty-eight 25-75 year-old adults read sentences with high cloze (HC) and low cloze (LC) probability while functional magnetic resonance imaging was conducted. Significant age-related reduction of cloze effect (LC vs. HC) was found in several regions, especially the left middle frontal gyrus (MFG) and ri...

  19. XML databases and the semantic web

    CERN Document Server

    Thuraisingham, Bhavani

    2002-01-01

    Efficient access to data, sharing data, extracting information from data, and making use of the information have become urgent needs for today''s corporations. With so much data on the Web, managing it with conventional tools is becoming almost impossible. New tools and techniques are necessary to provide interoperability as well as warehousing between multiple data sources and systems, and to extract information from the databases. XML Databases and the Semantic Web focuses on critical and new Web technologies needed for organizations to carry out transactions on the Web, to understand how to use the Web effectively, and to exchange complex documents on the Web.This reference for database administrators, database designers, and Web designers working in tandem with database technologists covers three emerging technologies of significant impact for electronic business: Extensible Markup Language (XML), semi-structured databases, and the semantic Web. The first two parts of the book explore these emerging techn...

  20. Why all the confusion? Experimental task explains discrepant semantic priming effects in schizophrenia under "automatic" conditions: evidence from Event-Related Potentials.

    Science.gov (United States)

    Kreher, Donna A; Goff, Donald; Kuperberg, Gina R

    2009-06-01

    The schizophrenia research literature contains many differing accounts of semantic memory function in schizophrenia as assessed through the semantic priming paradigm. Most recently, Event-Related Potentials (ERPs) have been used to demonstrate both increased and decreased semantic priming at a neural level in schizophrenia patients, relative to healthy controls. The present study used ERPs to investigate the role of behavioral task in determining neural semantic priming effects in schizophrenia. The same schizophrenia patients and healthy controls completed two experiments in which word stimuli were identical, and the time between the onset of prime and target remained constant at 350 ms: in the first, participants monitored for words within a particular semantic category that appeared only in filler items (implicit task); in the second, participants explicitly rated the relatedness of word-pairs (explicit task). In the explicit task, schizophrenia patients showed reduced direct and indirect semantic priming in comparison with healthy controls. In contrast, in the implicit task, schizophrenia patients showed normal or, in positively thought-disordered patients, increased direct and indirect N400 priming effects compared with healthy controls. These data confirm that, although schizophrenia patients with positive thought disorder may show an abnormally increased automatic spreading activation, the introduction of semantic decision-making can result in abnormally reduced semantic priming in schizophrenia, even when other experimental conditions bias toward automatic processing.

  1. Preserved musical semantic memory in semantic dementia.

    Science.gov (United States)

    Weinstein, Jessica; Koenig, Phyllis; Gunawardena, Delani; McMillan, Corey; Bonner, Michael; Grossman, Murray

    2011-02-01

    To understand the scope of semantic impairment in semantic dementia. Case study. Academic medical center. A man with semantic dementia, as demonstrated by clinical, neuropsychological, and imaging studies. Music performance and magnetic resonance imaging results. Despite profoundly impaired semantic memory for words and objects due to left temporal lobe atrophy, this semiprofessional musician was creative and expressive in demonstrating preserved musical knowledge. Long-term representations of words and objects in semantic memory may be dissociated from meaningful knowledge in other domains, such as music.

  2. Semantic Activity Recognition

    OpenAIRE

    Thonnat , Monique

    2008-01-01

    International audience; Extracting automatically the semantics from visual data is a real challenge. We describe in this paper how recent work in cognitive vision leads to significative results in activity recognition for visualsurveillance and video monitoring. In particular we present work performed in the domain of video understanding in our PULSAR team at INRIA in Sophia Antipolis. Our main objective is to analyse in real-time video streams captured by static video cameras and to recogniz...

  3. A Semantic Web-based System for Mining Genetic Mutations in Cancer Clinical Trials.

    Science.gov (United States)

    Priya, Sambhawa; Jiang, Guoqian; Dasari, Surendra; Zimmermann, Michael T; Wang, Chen; Heflin, Jeff; Chute, Christopher G

    2015-01-01

    Textual eligibility criteria in clinical trial protocols contain important information about potential clinically relevant pharmacogenomic events. Manual curation for harvesting this evidence is intractable as it is error prone and time consuming. In this paper, we develop and evaluate a Semantic Web-based system that captures and manages mutation evidences and related contextual information from cancer clinical trials. The system has 2 main components: an NLP-based annotator and a Semantic Web ontology-based annotation manager. We evaluated the performance of the annotator in terms of precision and recall. We demonstrated the usefulness of the system by conducting case studies in retrieving relevant clinical trials using a collection of mutations identified from TCGA Leukemia patients and Atlas of Genetics and Cytogenetics in Oncology and Haematology. In conclusion, our system using Semantic Web technologies provides an effective framework for extraction, annotation, standardization and management of genetic mutations in cancer clinical trials.

  4. Analysis and visualization of disease courses in a semantically-enabled cancer registry.

    Science.gov (United States)

    Esteban-Gil, Angel; Fernández-Breis, Jesualdo Tomás; Boeker, Martin

    2017-09-29

    Regional and epidemiological cancer registries are important for cancer research and the quality management of cancer treatment. Many technological solutions are available to collect and analyse data for cancer registries nowadays. However, the lack of a well-defined common semantic model is a problem when user-defined analyses and data linking to external resources are required. The objectives of this study are: (1) design of a semantic model for local cancer registries; (2) development of a semantically-enabled cancer registry based on this model; and (3) semantic exploitation of the cancer registry for analysing and visualising disease courses. Our proposal is based on our previous results and experience working with semantic technologies. Data stored in a cancer registry database were transformed into RDF employing a process driven by OWL ontologies. The semantic representation of the data was then processed to extract semantic patient profiles, which were exploited by means of SPARQL queries to identify groups of similar patients and to analyse the disease timelines of patients. Based on the requirements analysis, we have produced a draft of an ontology that models the semantics of a local cancer registry in a pragmatic extensible way. We have implemented a Semantic Web platform that allows transforming and storing data from cancer registries in RDF. This platform also permits users to formulate incremental user-defined queries through a graphical user interface. The query results can be displayed in several customisable ways. The complex disease timelines of individual patients can be clearly represented. Different events, e.g. different therapies and disease courses, are presented according to their temporal and causal relations. The presented platform is an example of the parallel development of ontologies and applications that take advantage of semantic web technologies in the medical field. The semantic structure of the representation renders it easy to

  5. Competitive Semantic Memory Retrieval: Temporal Dynamics Revealed by Event-Related Potentials.

    Directory of Open Access Journals (Sweden)

    Robin Hellerstedt

    Full Text Available Memories compete for retrieval when they are related to a common retrieval cue. Previous research has shown that retrieval of a target memory may lead to subsequent retrieval-induced forgetting (RIF of currently irrelevant competing memories. In the present study, we investigated the time course of competitive semantic retrieval and examined the neurocognitive mechanisms underlying RIF. We contrasted two theoretical accounts of RIF by examining a critical aspect of this memory phenomenon, namely the extent to which it depends on successful retrieval of the target memory. Participants first studied category-exemplar word-pairs (e.g. Fruit-Apple. Next, we recorded electrophysiological measures of brain activity while the participants performed a competitive semantic cued-recall task. In this task, the participants were provided with the studied categories but they were instructed to retrieve other unstudied exemplars (e.g. Fruit-Ma__?. We investigated the event-related potential (ERP correlates of retrieval success by comparing ERPs from successful and failed retrieval trials. To isolate the ERP correlates of continuous retrieval attempts from the ERP correlates of retrieval success, we included an impossible retrieval condition, with incompletable word-stem cues (Drinks-Wy__ and compared it with a non-retrieval presentation baseline condition (Occupation-Dentist. The participants' memory for all the studied exemplars was tested in the final phase of the experiment. Taken together, the behavioural results suggest that RIF is independent of target retrieval. Beyond investigating the mechanisms underlying RIF, the present study also elucidates the temporal dynamics of semantic cued-recall by isolating the ERP correlates of retrieval attempt and retrieval success. The ERP results revealed that retrieval attempt is reflected in a late posterior negativity, possibly indicating construction of candidates for completing the word-stem cue and retrieval

  6. Competitive Semantic Memory Retrieval: Temporal Dynamics Revealed by Event-Related Potentials

    Science.gov (United States)

    Hellerstedt, Robin; Johansson, Mikael

    2016-01-01

    Memories compete for retrieval when they are related to a common retrieval cue. Previous research has shown that retrieval of a target memory may lead to subsequent retrieval-induced forgetting (RIF) of currently irrelevant competing memories. In the present study, we investigated the time course of competitive semantic retrieval and examined the neurocognitive mechanisms underlying RIF. We contrasted two theoretical accounts of RIF by examining a critical aspect of this memory phenomenon, namely the extent to which it depends on successful retrieval of the target memory. Participants first studied category-exemplar word-pairs (e.g. Fruit—Apple). Next, we recorded electrophysiological measures of brain activity while the participants performed a competitive semantic cued-recall task. In this task, the participants were provided with the studied categories but they were instructed to retrieve other unstudied exemplars (e.g. Fruit—Ma__?). We investigated the event-related potential (ERP) correlates of retrieval success by comparing ERPs from successful and failed retrieval trials. To isolate the ERP correlates of continuous retrieval attempts from the ERP correlates of retrieval success, we included an impossible retrieval condition, with incompletable word-stem cues (Drinks—Wy__) and compared it with a non-retrieval presentation baseline condition (Occupation—Dentist). The participants’ memory for all the studied exemplars was tested in the final phase of the experiment. Taken together, the behavioural results suggest that RIF is independent of target retrieval. Beyond investigating the mechanisms underlying RIF, the present study also elucidates the temporal dynamics of semantic cued-recall by isolating the ERP correlates of retrieval attempt and retrieval success. The ERP results revealed that retrieval attempt is reflected in a late posterior negativity, possibly indicating construction of candidates for completing the word-stem cue and retrieval

  7. Competitive Semantic Memory Retrieval: Temporal Dynamics Revealed by Event-Related Potentials.

    Science.gov (United States)

    Hellerstedt, Robin; Johansson, Mikael

    2016-01-01

    Memories compete for retrieval when they are related to a common retrieval cue. Previous research has shown that retrieval of a target memory may lead to subsequent retrieval-induced forgetting (RIF) of currently irrelevant competing memories. In the present study, we investigated the time course of competitive semantic retrieval and examined the neurocognitive mechanisms underlying RIF. We contrasted two theoretical accounts of RIF by examining a critical aspect of this memory phenomenon, namely the extent to which it depends on successful retrieval of the target memory. Participants first studied category-exemplar word-pairs (e.g. Fruit-Apple). Next, we recorded electrophysiological measures of brain activity while the participants performed a competitive semantic cued-recall task. In this task, the participants were provided with the studied categories but they were instructed to retrieve other unstudied exemplars (e.g. Fruit-Ma__?). We investigated the event-related potential (ERP) correlates of retrieval success by comparing ERPs from successful and failed retrieval trials. To isolate the ERP correlates of continuous retrieval attempts from the ERP correlates of retrieval success, we included an impossible retrieval condition, with incompletable word-stem cues (Drinks-Wy__) and compared it with a non-retrieval presentation baseline condition (Occupation-Dentist). The participants' memory for all the studied exemplars was tested in the final phase of the experiment. Taken together, the behavioural results suggest that RIF is independent of target retrieval. Beyond investigating the mechanisms underlying RIF, the present study also elucidates the temporal dynamics of semantic cued-recall by isolating the ERP correlates of retrieval attempt and retrieval success. The ERP results revealed that retrieval attempt is reflected in a late posterior negativity, possibly indicating construction of candidates for completing the word-stem cue and retrieval monitoring

  8. QTLTableMiner++: semantic mining of QTL tables in scientific articles.

    Science.gov (United States)

    Singh, Gurnoor; Kuzniar, Arnold; van Mulligen, Erik M; Gavai, Anand; Bachem, Christian W; Visser, Richard G F; Finkers, Richard

    2018-05-25

    A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner ++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats.

  9. The role of medial temporal lobe in retrieving spatial and nonspatial relations from episodic and semantic memory.

    Science.gov (United States)

    Ryan, Lee; Lin, Chun-Yu; Ketcham, Katie; Nadel, Lynn

    2010-01-01

    This study examined the involvement of medial temporal lobe, especially the hippocampus, in processing spatial and nonspatial relations using episodic and semantic versions of a relational judgment task. Participants studied object arrays and were tested on different types of relations between pairs of objects. Three prevalent views of hippocampal function were considered. Cognitive map theory (O'Keefe and Nadel (1978) The Hippocampus as a Cognitive Map. USA: Oxford University Press) emphasizes hippocampal involvement in spatial relational tasks. Multiple trace theory (Nadel and Moscovitch (1997) Memory consolidation, retrograde amnesia and the hippocampal complex Curr Opin Neurobiol 7:217-227) emphasizes hippocampal involvement in episodic tasks. Eichenbaum and Cohen's ((2001) From Conditioning to Conscious Recollection: Memory Systems of the Brain. USA: Oxford University Press) relational theory predicts equivalent hippocampal involvement in all relational tasks within both semantic and episodic memory. The fMRI results provided partial support for all three theories, though none of them fit the data perfectly. We observed hippocampal activation during all relational tasks, with increased activation for spatial compared to nonspatial relations, and for episodic compared to semantic relations. The placement of activation along the anterior-posterior axis of the hippocampus also differentiated the conditions. We suggest a view of hippocampal function in memory that incorporates aspects of all three theories. Copyright 2009 Wiley-Liss, Inc.

  10. Semantic similarity measures in the biomedical domain by leveraging a web search engine.

    Science.gov (United States)

    Hsieh, Sheau-Ling; Chang, Wen-Yung; Chen, Chi-Huang; Weng, Yung-Ching

    2013-07-01

    Various researches in web related semantic similarity measures have been deployed. However, measuring semantic similarity between two terms remains a challenging task. The traditional ontology-based methodologies have a limitation that both concepts must be resided in the same ontology tree(s). Unfortunately, in practice, the assumption is not always applicable. On the other hand, if the corpus is sufficiently adequate, the corpus-based methodologies can overcome the limitation. Now, the web is a continuous and enormous growth corpus. Therefore, a method of estimating semantic similarity is proposed via exploiting the page counts of two biomedical concepts returned by Google AJAX web search engine. The features are extracted as the co-occurrence patterns of two given terms P and Q, by querying P, Q, as well as P AND Q, and the web search hit counts of the defined lexico-syntactic patterns. These similarity scores of different patterns are evaluated, by adapting support vector machines for classification, to leverage the robustness of semantic similarity measures. Experimental results validating against two datasets: dataset 1 provided by A. Hliaoutakis; dataset 2 provided by T. Pedersen, are presented and discussed. In dataset 1, the proposed approach achieves the best correlation coefficient (0.802) under SNOMED-CT. In dataset 2, the proposed method obtains the best correlation coefficient (SNOMED-CT: 0.705; MeSH: 0.723) with physician scores comparing with measures of other methods. However, the correlation coefficients (SNOMED-CT: 0.496; MeSH: 0.539) with coder scores received opposite outcomes. In conclusion, the semantic similarity findings of the proposed method are close to those of physicians' ratings. Furthermore, the study provides a cornerstone investigation for extracting fully relevant information from digitizing, free-text medical records in the National Taiwan University Hospital database.

  11. COTARD SYNDROME IN SEMANTIC DEMENTIA

    Science.gov (United States)

    Mendez, Mario F.; Ramírez-Bermúdez, Jesús

    2011-01-01

    Background Semantic dementia is a neurodegenerative disorder characterized by the loss of meaning of words or concepts. semantic dementia can offer potential insights into the mechanisms of content-specific delusions. Objective The authors present a rare case of semantic dementia with Cotard syndrome, a delusion characterized by nihilism or self-negation. Method The semantic deficits and other features of semantic dementia were evaluated in relation to the patient's Cotard syndrome. Results Mrs. A developed the delusional belief that she was wasting and dying. This occurred after she lost knowledge for her somatic discomforts and sensations and for the organs that were the source of these sensations. Her nihilistic beliefs appeared to emerge from her misunderstanding of her somatic sensations. Conclusion This unique patient suggests that a mechanism for Cotard syndrome is difficulty interpreting the nature and source of internal pains and sensations. We propose that loss of semantic knowledge about one's own body may lead to the delusion of nihilism or death. PMID:22054629

  12. Semantic, syntactic, and phonological processing of written words in adult developmental dyslexic readers: an event-related brain potential study

    Directory of Open Access Journals (Sweden)

    Johannes Sönke

    2007-07-01

    Full Text Available Abstract Background The present study used event-related brain potentials to investigate semantic, phonological and syntactic processes in adult German dyslexic and normal readers in a word reading task. Pairs of German words were presented one word at a time. Subjects had to perform a semantic judgment task (house – window; are they semantically related?, a rhyme judgment task (house – mouse; do they rhyme? and a gender judgment task (das – Haus [the – house]; is the gender correct? [in German, house has a neutral gender: das Haus]. Results Normal readers responded faster compared to dyslexic readers in all three tasks. Onset latencies of the N400 component were delayed in dyslexic readers in the rhyme judgment and in the gender judgment task, but not in the semantic judgment task. N400 and the anterior negativity peak amplitudes did not differ between the two groups. However, the N400 persisted longer in the dyslexic group in the rhyme judgment and in the semantic judgment tasks. Conclusion These findings indicate that dyslexics are phonologically impaired (delayed N400 in the rhyme judgment task but that they also have difficulties in other, non-phonological aspects of reading (longer response times, longer persistence of the N400. Specifically, semantic and syntactic integration seem to require more effort for dyslexic readers and take longer irrespective of the reading task that has to be performed.

  13. Somatotopic Semantic Priming and Prediction in the Motor System

    Science.gov (United States)

    Grisoni, Luigi; Dreyer, Felix R.; Pulvermüller, Friedemann

    2016-01-01

    The recognition of action-related sounds and words activates motor regions, reflecting the semantic grounding of these symbols in action information; in addition, motor cortex exerts causal influences on sound perception and language comprehension. However, proponents of classic symbolic theories still dispute the role of modality-preferential systems such as the motor cortex in the semantic processing of meaningful stimuli. To clarify whether the motor system carries semantic processes, we investigated neurophysiological indexes of semantic relationships between action-related sounds and words. Event-related potentials revealed that action-related words produced significantly larger stimulus-evoked (Mismatch Negativity-like) and predictive brain responses (Readiness Potentials) when presented in body-part-incongruent sound contexts (e.g., “kiss” in footstep sound context; “kick” in whistle context) than in body-part-congruent contexts, a pattern reminiscent of neurophysiological correlates of semantic priming. Cortical generators of the semantic relatedness effect were localized in areas traditionally associated with semantic memory, including left inferior frontal cortex and temporal pole, and, crucially, in motor areas, where body-part congruency of action sound–word relationships was indexed by a somatotopic pattern of activation. As our results show neurophysiological manifestations of action-semantic priming in the motor cortex, they prove semantic processing in the motor system and thus in a modality-preferential system of the human brain. PMID:26908635

  14. Semantic relation vs. surprise: the differential effects of related and unrelated co-verbal gestures on neural encoding and subsequent recognition.

    Science.gov (United States)

    Straube, Benjamin; Meyer, Lea; Green, Antonia; Kircher, Tilo

    2014-06-03

    Speech-associated gesturing leads to memory advantages for spoken sentences. However, unexpected or surprising events are also likely to be remembered. With this study we test the hypothesis that different neural mechanisms (semantic elaboration and surprise) lead to memory advantages for iconic and unrelated gestures. During fMRI-data acquisition participants were presented with video clips of an actor verbalising concrete sentences accompanied by iconic gestures (IG; e.g., circular gesture; sentence: "The man is sitting at the round table"), unrelated free gestures (FG; e.g., unrelated up down movements; same sentence) and no gestures (NG; same sentence). After scanning, recognition performance for the three conditions was tested. Videos were evaluated regarding semantic relation and surprise by a different group of participants. The semantic relationship between speech and gesture was rated higher for IG (IG>FG), whereas surprise was rated higher for FG (FG>IG). Activation of the hippocampus correlated with subsequent memory performance of both gesture conditions (IG+FG>NG). For the IG condition we found activation in the left temporal pole and middle cingulate cortex (MCC; IG>FG). In contrast, for the FG condition posterior thalamic structures (FG>IG) as well as anterior and posterior cingulate cortices were activated (FG>NG). Our behavioral and fMRI-data suggest different mechanisms for processing related and unrelated co-verbal gestures, both of them leading to enhanced memory performance. Whereas activation in MCC and left temporal pole for iconic co-verbal gestures may reflect semantic memory processes, memory enhancement for unrelated gestures relies on the surprise response, mediated by anterior/posterior cingulate cortex and thalamico-hippocampal structures. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Semantic Analysis of FBI News Reports

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah

    2012-01-01

    In this paper we present our work on semantic analysis of FBI News reports. In the paper we have considered the News which are of the immense significance for the analyst who want to analyze the News of specific area. With this definite analysis we are able to extract critical events or concepts...

  16. Event-Related EEG Oscillations to Semantically Unrelated Words in Normal and Learning Disabled Children

    Science.gov (United States)

    Fernandez, Thalia; Harmony, Thalia; Mendoza, Omar; Lopez-Alanis, Paula; Marroquin, Jose Luis; Otero, Gloria; Ricardo-Garcell, Josefina

    2012-01-01

    Learning disabilities (LD) are one of the most frequent problems for elementary school-aged children. In this paper, event-related EEG oscillations to semantically related and unrelated pairs of words were studied in a group of 18 children with LD not otherwise specified (LD-NOS) and in 16 children with normal academic achievement. We propose that…

  17. SEMANTIC WEB MINING: ISSUES AND CHALLENGES

    OpenAIRE

    Karan Singh*, Anil kumar, Arun Kumar Yadav

    2016-01-01

    The combination of the two fast evolving scientific research areas “Semantic Web” and “Web Mining” are well-known as “Semantic Web Mining” in computer science. These two areas cover way for the mining of related and meaningful information from the web, by this means giving growth to the term “Semantic Web Mining”. The “Semantic Web” makes mining easy and “Web Mining” can construct new structure of Web. Web Mining applies Data Mining technique on web content, Structure and Usage. This paper gi...

  18. Solving Guesstimation Problems Using the Semantic Web:Four Lessons from an Application

    OpenAIRE

    Bundy, Alan; Sasnauskas, Gintautas; Chan, Michael

    2013-01-01

    We draw on our experience of implementing a semi-automated guesstimation application of the Semantic Web, gort, to draw four lessons, which we claim are of general applicability. These are:1. Inference can unleash the Semantic Web: The full power of the web will only be realised when we can use it to infer new knowledge from old.2. The Semantic Web does not constrain the inference mechanisms: Since we must anyway curate the knowledge we extract from the web, we can take the opportunity to tra...

  19. Learning semantic histopathological representation for basal cell carcinoma classification

    Science.gov (United States)

    Gutiérrez, Ricardo; Rueda, Andrea; Romero, Eduardo

    2013-03-01

    Diagnosis of a histopathology glass slide is a complex process that involves accurate recognition of several structures, their function in the tissue and their relation with other structures. The way in which the pathologist represents the image content and the relations between those objects yields a better and accurate diagnoses. Therefore, an appropriate semantic representation of the image content will be useful in several analysis tasks such as cancer classification, tissue retrieval and histopahological image analysis, among others. Nevertheless, to automatically recognize those structures and extract their inner semantic meaning are still very challenging tasks. In this paper we introduce a new semantic representation that allows to describe histopathological concepts suitable for classification. The approach herein identify local concepts using a dictionary learning approach, i.e., the algorithm learns the most representative atoms from a set of random sampled patches, and then models the spatial relations among them by counting the co-occurrence between atoms, while penalizing the spatial distance. The proposed approach was compared with a bag-of-features representation in a tissue classification task. For this purpose, 240 histological microscopical fields of view, 24 per tissue class, were collected. Those images fed a Support Vector Machine classifier per class, using 120 images as train set and the remaining ones for testing, maintaining the same proportion of each concept in the train and test sets. The obtained classification results, averaged from 100 random partitions of training and test sets, shows that our approach is more sensitive in average than the bag-of-features representation in almost 6%.

  20. Semantic attributes for people's appearance description: an appearance modality for video surveillance applications

    Science.gov (United States)

    Frikha, Mayssa; Fendri, Emna; Hammami, Mohamed

    2017-09-01

    Using semantic attributes such as gender, clothes, and accessories to describe people's appearance is an appealing modeling method for video surveillance applications. We proposed a midlevel appearance signature based on extracting a list of nameable semantic attributes describing the body in uncontrolled acquisition conditions. Conventional approaches extract the same set of low-level features to learn the semantic classifiers uniformly. Their critical limitation is the inability to capture the dominant visual characteristics for each trait separately. The proposed approach consists of extracting low-level features in an attribute-adaptive way by automatically selecting the most relevant features for each attribute separately. Furthermore, relying on a small training-dataset would easily lead to poor performance due to the large intraclass and interclass variations. We annotated large scale people images collected from different person reidentification benchmarks covering a large attribute sample and reflecting the challenges of uncontrolled acquisition conditions. These annotations were gathered into an appearance semantic attribute dataset that contains 3590 images annotated with 14 attributes. Various experiments prove that carefully designed features for learning the visual characteristics for an attribute provide an improvement of the correct classification accuracy and a reduction of both spatial and temporal complexities against state-of-the-art approaches.

  1. Maternal talk in cognitive development: relations between psychological lexicon, semantic development, empathy and temperament

    Directory of Open Access Journals (Sweden)

    Dolores eRollo

    2016-03-01

    Full Text Available In this study, we investigated the relationship between mothers’ psychological lexicon and children’s cognitive and socio-emotive development as assessed through conceptual and semantic understanding tasks, in addition to the traditional tasks of theory of mind. Currently, there is considerable evidence to suggest that the frequency of mothers’ mental state words used in mother-child picture-book reading is linked with children’s theory of mind skills. Furthermore, mothers’ use of cognitive terms is more strongly related to children’s theory of mind performances than the mothers’ references to other mental states, such as desires or emotions (Rollo, Buttiglieri, 2009. Current literature has established that early maternal input is related to later child mental state understanding; however it has not yet clarified which maternal terms are most useful for the socio-emotional and cognitive development of the child, and which aspect of the cognitive development benefits from the mother-child interaction.The present study addresses this issue and focuses on the relationship between mothers’ mental state talk and children’s behavior in conceptual and semantic tasks, and in a theory of mind task.In this study fifty pairs consisting of mothers and their 3 to 6-year-old children participated in two sessions: (1 The mothers read a picture book to their children. To assess the maternal psychological lexicon, their narrative was codified according to the categories of mental state references used in literature: perceptual, emotional, volitional, cognitive, moral and communicative. (2 After a few days, the conceptual and semantic skills of the children (tasks of contextualization and classification, memory and definition of words and their psychological lexicon were assessed.The results suggest close links between the frequency and variety of mothers’ mental state words and some semantic and conceptual skills of children.

  2. Semantic and episodic memory of music are subserved by distinct neural networks.

    Science.gov (United States)

    Platel, Hervé; Baron, Jean-Claude; Desgranges, Béatrice; Bernard, Frédéric; Eustache, Francis

    2003-09-01

    Numerous functional imaging studies have shown that retrieval from semantic and episodic memory is subserved by distinct neural networks. However, these results were essentially obtained with verbal and visuospatial material. The aim of this work was to determine the neural substrates underlying the semantic and episodic components of music using familiar and nonfamiliar melodic tunes. To study musical semantic memory, we designed a task in which the instruction was to judge whether or not the musical extract was felt as "familiar." To study musical episodic memory, we constructed two delayed recognition tasks, one containing only familiar and the other only nonfamiliar items. For each recognition task, half of the extracts (targets) were presented in the prior semantic task. The episodic and semantic tasks were to be contrasted by a comparison to two perceptive control tasks and to one another. Cerebral blood flow was assessed by means of the oxygen-15-labeled water injection method, using high-resolution PET. Distinct patterns of activations were found. First, regarding the episodic memory condition, bilateral activations of the middle and superior frontal gyri and precuneus (more prominent on the right side) were observed. Second, the semantic memory condition disclosed extensive activations in the medial and orbital frontal cortex bilaterally, the left angular gyrus, and predominantly the left anterior part of the middle temporal gyri. The findings from this study are discussed in light of the available neuropsychological data obtained in brain-damaged subjects and functional neuroimaging studies.

  3. On the Semantics of Focus

    Science.gov (United States)

    Kess, Joseph F.

    1975-01-01

    This article discusses the semantics of the notion of focus, insofar as it relates to Filipino languages. The evolution of this notion is reviewed, and an alternative explanation of it is given, stressing the fact that grammar and semantics should be kept separate in a discussion of focus. (CLK)

  4. Inter-deriving Semantic Artifacts for Object-Oriented Programming

    DEFF Research Database (Denmark)

    Danvy, Olivier; Johannsen, Jacob

    2008-01-01

    .e., big-step operational semantics) specified in Abadi and Cardelli's monograph. This abstract machine therefore embodies the soundness of Abadi and Cardelli's reduction semantics and natural semantics relative to each other. To move closer to actual implementations, which use environments rather than......We present a new abstract machine for Abadi and Cardelli's untyped calculus of objects. What is special about this semantic artifact (i.e., man-made construct) is that is mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i...... actual substitutions, we then represent object methods as closures and in the same inter-derivational spirit, we present three new semantic artifacts: a reduction semantics for a version of Abadi and Cardelli's untyped calculus of objects with explicit substitutions, an environment-based abstract machine...

  5. Model for Semantically Rich Point Cloud Data

    Science.gov (United States)

    Poux, F.; Neuville, R.; Hallot, P.; Billen, R.

    2017-10-01

    This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

  6. MODEL FOR SEMANTICALLY RICH POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    F. Poux

    2017-10-01

    Full Text Available This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

  7. A Validation of Parafoveal Semantic Information Extraction in Reading Chinese

    Science.gov (United States)

    Zhou, Wei; Kliegl, Reinhold; Yan, Ming

    2013-01-01

    Parafoveal semantic processing has recently been well documented in reading Chinese sentences, presumably because of language-specific features. However, because of a large variation of fixation landing positions on pretarget words, some preview words actually were located in foveal vision when readers' eyes landed close to the end of the…

  8. Improving life sciences information retrieval using semantic web technology.

    Science.gov (United States)

    Quan, Dennis

    2007-05-01

    The ability to retrieve relevant information is at the heart of every aspect of research and development in the life sciences industry. Information is often distributed across multiple systems and recorded in a way that makes it difficult to piece together the complete picture. Differences in data formats, naming schemes and network protocols amongst information sources, both public and private, must be overcome, and user interfaces not only need to be able to tap into these diverse information sources but must also assist users in filtering out extraneous information and highlighting the key relationships hidden within an aggregated set of information. The Semantic Web community has made great strides in proposing solutions to these problems, and many efforts are underway to apply Semantic Web techniques to the problem of information retrieval in the life sciences space. This article gives an overview of the principles underlying a Semantic Web-enabled information retrieval system: creating a unified abstraction for knowledge using the RDF semantic network model; designing semantic lenses that extract contextually relevant subsets of information; and assembling semantic lenses into powerful information displays. Furthermore, concrete examples of how these principles can be applied to life science problems including a scenario involving a drug discovery dashboard prototype called BioDash are provided.

  9. Semantic content-based recommendations using semantic graphs.

    Science.gov (United States)

    Guo, Weisen; Kraines, Steven B

    2010-01-01

    Recommender systems (RSs) can be useful for suggesting items that might be of interest to specific users. Most existing content-based recommendation (CBR) systems are designed to recommend items based on text content, and the items in these systems are usually described with keywords. However, similarity evaluations based on keywords suffer from the ambiguity of natural languages. We present a semantic CBR method that uses Semantic Web technologies to recommend items that are more similar semantically with the items that the user prefers. We use semantic graphs to represent the items and we calculate the similarity scores for each pair of semantic graphs using an inverse graph frequency algorithm. The items having higher similarity scores to the items that are known to be preferred by the user are recommended.

  10. SEMANTIC SEGMENTATION OF BUILDING ELEMENTS USING POINT CLOUD HASHING

    Directory of Open Access Journals (Sweden)

    M. Chizhova

    2018-05-01

    Full Text Available For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect into different building types and structural elements (dome, nave, transept etc., including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling.

  11. Semantic Search in E-Discovery: An Interdisciplinary Approach

    NARCIS (Netherlands)

    Graus, D.; Ren, Z.; de Rijke, M.; van Dijk, D.; Henseler, H.; van der Knaap, N.

    2013-01-01

    We propose an interdisciplinary approach to applying and evaluating semantic search in the e-discovery setting. By combining expertise from the fields of law and criminology with that of information retrieval and extraction, we move beyond "algorithm-centric" evaluation, towards evaluating the

  12. Relation Extraction with Weak Supervision and Distributional Semantics

    Science.gov (United States)

    2013-05-01

    country is no longer a member of the organization), a player and an event, a team and a sport, etc. Multiple meanings of a relation phrase are success ...Zimbabwe, the Commonwealth> <force, country> <American forces, Vietnam>; <Roman Legions, Britain> < player , event> <Brandon Bass, the NBA draft>; <Agassi...training data. We found that dealing with incorrectly labeled examples is critical for its success . We develop a latent Bayesian framework for this

  13. Examining lateralized semantic access using pictures.

    Science.gov (United States)

    Lovseth, Kyle; Atchley, Ruth Ann

    2010-03-01

    A divided visual field (DVF) experiment examined the semantic processing strategies employed by the cerebral hemispheres to determine if strategies observed with written word stimuli generalize to other media for communicating semantic information. We employed picture stimuli and vary the degree of semantic relatedness between the picture pairs. Participants made an on-line semantic relatedness judgment in response to sequentially presented pictures. We found that when pictures are presented to the right hemisphere responses are generally more accurate than the left hemisphere for semantic relatedness judgments for picture pairs. Furthermore, consistent with earlier DVF studies employing words, we conclude that the RH is better at accessing or maintaining access to information that has a weak or more remote semantic relationship. We also found evidence of faster access for pictures presented to the LH in the strongly-related condition. Overall, these results are consistent with earlier DVF word studies that argue that the cerebral hemispheres each play an important and separable role during semantic retrieval. Copyright 2009 Elsevier Inc. All rights reserved.

  14. An enhanced model for automatically extracting topic phrase from ...

    African Journals Online (AJOL)

    The key benefit foreseen from this automatic document classification is not only related to search engines, but also to many other fields like, document organization, text filtering and semantic index managing. Key words: Keyphrase extraction, machine learning, search engine snippet, document classification, topic tracking ...

  15. Incorporating Relation Paths in Neural Relation Extraction

    OpenAIRE

    Zeng, Wenyuan; Lin, Yankai; Liu, Zhiyuan; Sun, Maosong

    2016-01-01

    Distantly supervised relation extraction has been widely used to find novel relational facts from plain text. To predict the relation between a pair of two target entities, existing methods solely rely on those direct sentences containing both entities. In fact, there are also many sentences containing only one of the target entities, which provide rich and useful information for relation extraction. To address this issue, we build inference chains between two target entities via intermediate...

  16. Preserved semantic priming effect in alexia.

    Science.gov (United States)

    Mimura, M; Goodglass, H; Milberg, W

    1996-09-01

    BH, a left-handed patient with alexia and nonfluent aphasia, was presented with a lexical-decision task in which words and pronounceable pseudowords were preceded by semantically related or unrelated picture primes (Experiment 1). In Experiment 2, BH was given an explicit reading task using the word lists from Experiment 1. Performance on Experiment 2 disclosed severe reading deficits in both oral reading and semantic matching of the words to pictures. However, in Experiment 1, BH demonstrated a significant semantic priming effect, responding more accurately and more quickly to words preceded by related primes than by unrelated primes. The present results suggest that even in a patient with severe alexia, implicit access to semantic information can be preserved in the absence of explicit identification. The possibility of categorical gradient in implicit activation (living vs. nonliving) in BH was also discussed, which, however, needs to be clarified in the further investigation.

  17. Semantic priming without association: a meta-analytic review.

    Science.gov (United States)

    Lucas, M

    2000-12-01

    A meta-analysis of 26 studies indicated that automatic semantic priming can occur without association. Priming did not vary substantially with differences in variables that affect automatic versus strategic processing, such as time spent processing the prime and target, relationship proportion, and task (except that average effects were smaller in the naming task). Although category coordinates were investigated in the majority of studies, synonyms, antonyms, and script relations also demonstrated priming; functional relations showed greater priming, and essential and perceptual relations showed less. The average effect size for semantic priming was smaller than that for associative priming, suggesting that there is an "associative boost" from adding an associative relationship to a semantic one. The implications of these findings for the modularity thesis and for models of semantic priming are discussed.

  18. A Lexical Framework for Semantic Annotation of Positive and Negative Regulation Relations in Biomedical Pathways

    DEFF Research Database (Denmark)

    Zambach, Sine; Lassen, Tine

    presented here, we analyze 6 frequently used verbs denoting the regulation relations regulates, positively regulates and negatively regulates through corpus analysis, and propose a formal representation of the acquired knowledge as domain speci¯c semantic frames. The acquired knowledge patterns can thus...

  19. Scandinavian Semantics and the Human Body

    DEFF Research Database (Denmark)

    Levisen, Carsten

    2015-01-01

    , it is demonstrated that Scandinavian and English systems differ significantly in some aspects of the way in which the construe the human body with words. The study ventures an innovative combination of methods, pairing the Natural Semantic Metalanguage (NSM) approach to linguistic and conceptual analysis......This paper presents an ethnolinguistic analysis of how the space between the head and the body is construed in Scandinavian semantic systems vis-a-vis the semantic system of English. With an extensive case study of neck-related meanings in Danish, and with cross-Scandinavian reference...... with empirical evidence from the Evolution of Semantic Systems (EoSS) project. This combination of empirical and interpretative tools helps to integrate evidence from semantics and semiotics, pinning out in great detail the intricacies of the meanings of particular body words. The paper concludes that body words...

  20. The facilitation effect of associative and semantic relatedness in word recognition

    Directory of Open Access Journals (Sweden)

    Jakić Milena

    2011-01-01

    Full Text Available In this study we addressed three issues concerning semantic and associative relatedness between two words and how they prime each other. The first issue is whether there is a priming effect of semantic relatedness over and above the effect of associative relatedness. The second issue is how difference in semantic overlap between two words affects priming. In order to specify the semantic overlap we introduce five relation types that differ in number of common semantic components. Three relation types (synonyms, antonyms and hyponyms represent semantic relatedness while two relation types represent associative relatedness, with negligible or no semantic relatedness. Finally, the third issue addressed in this study is whether there is a symmetric priming effect if we swap the position of prime and target, i.e. whether the direction of relatedness between two words affects priming. In two lexical decision experiments we presented five types of word pairs. In both experiments we obtained stronger facilitation for pairs that were both semantically and associatively related. Closer inspection showed that larger semantic overlap between words is paralleled by greater facilitation effect. The effects did not change when prime and target swap their position, indicating that the observed facilitation effects are symmetrical. This outcome complies with predictions of distributed models of memory.

  1. Learning semantic and visual similarity for endomicroscopy video retrieval.

    Science.gov (United States)

    Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

    2012-06-01

    Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them

  2. Episodic memory, semantic memory, and amnesia.

    Science.gov (United States)

    Squire, L R; Zola, S M

    1998-01-01

    Episodic memory and semantic memory are two types of declarative memory. There have been two principal views about how this distinction might be reflected in the organization of memory functions in the brain. One view, that episodic memory and semantic memory are both dependent on the integrity of medial temporal lobe and midline diencephalic structures, predicts that amnesic patients with medial temporal lobe/diencephalic damage should be proportionately impaired in both episodic and semantic memory. An alternative view is that the capacity for semantic memory is spared, or partially spared, in amnesia relative to episodic memory ability. This article reviews two kinds of relevant data: 1) case studies where amnesia has occurred early in childhood, before much of an individual's semantic knowledge has been acquired, and 2) experimental studies with amnesic patients of fact and event learning, remembering and knowing, and remote memory. The data provide no compelling support for the view that episodic and semantic memory are affected differently in medial temporal lobe/diencephalic amnesia. However, episodic and semantic memory may be dissociable in those amnesic patients who additionally have severe frontal lobe damage.

  3. The neural substrates of semantic memory deficits in early Alzheimer's disease: Clues from semantic priming effects and FDG-PET

    International Nuclear Information System (INIS)

    Giffard, B.; Laisney, M.; Mezenge, F.; De la Sayette, V.; Eustache, F.; Desgranges, B.

    2008-01-01

    The neural substrates responsible for semantic dysfunction during the early stages of AD have yet to be clearly identified. After a brief overview of the literature on normal and pathological semantic memory, we describe a new approach, designed to provide fresh insights into semantic deficits in AD. We mapped the correlations between resting-state brain glucose utilisation measured by FDG-PET and semantic priming scores in a group of 17 AD patients. The priming task, which yields a particularly pure measurement of semantic memory, was composed of related pairs of words sharing an attribute relationship (e.g. tiger-stripe). The priming scores correlated positively with the metabolism of the superior temporal areas on both sides, especially the right side, and this correlation was shown to be specific to the semantic priming effect.This pattern of results is discussed in the light of recent theoretical models of semantic memory, and suggests that a dysfunction of the right superior temporal cortex may contribute to early semantic deficits, characterised by the loss of specific features of concepts in AD. (authors)

  4. Effective Web and Desktop Retrieval with Enhanced Semantic Spaces

    Science.gov (United States)

    Daoud, Amjad M.

    We describe the design and implementation of the NETBOOK prototype system for collecting, structuring and efficiently creating semantic vectors for concepts, noun phrases, and documents from a corpus of free full text ebooks available on the World Wide Web. Automatic generation of concept maps from correlated index terms and extracted noun phrases are used to build a powerful conceptual index of individual pages. To ensure scalabilty of our system, dimension reduction is performed using Random Projection [13]. Furthermore, we present a complete evaluation of the relative effectiveness of the NETBOOK system versus the Google Desktop [8].

  5. Semantic coherence in English accusative-with-bare-infinitive constructions

    DEFF Research Database (Denmark)

    Jensen, Kim Ebensgaard

    2013-01-01

    -with-bare-infinitive construction. The main methodological framework is that of covarying collexeme analysis, which, through statistical corpus analysis, allows for the analyst to address the semantics of a construction. Using this method on data from the BNC, the ultimate purpose of the paper is to address the underlying semantic...... relations of English accusatives-with-bare-infinitives through the relations of semantic coherence between the two VPs....

  6. Discovery and Selection of Semantic Web Services

    CERN Document Server

    Wang, Xia

    2013-01-01

    For advanced web search engines to be able not only to search for semantically related information dispersed over different web pages, but also for semantic services providing certain functionalities, discovering semantic services is the key issue. Addressing four problems of current solution, this book presents the following contributions. A novel service model independent of semantic service description models is proposed, which clearly defines all elements necessary for service discovery and selection. It takes service selection as its gist and improves efficiency. Corresponding selection algorithms and their implementation as components of the extended Semantically Enabled Service-oriented Architecture in the Web Service Modeling Environment are detailed. Many applications of semantic web services, e.g. discovery, composition and mediation, can benefit from a general approach for building application ontologies. With application ontologies thus built, services are discovered in the same way as with single...

  7. Annotation and retrieval system of CAD models based on functional semantics

    Science.gov (United States)

    Wang, Zhansong; Tian, Ling; Duan, Wenrui

    2014-11-01

    CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs(AAG) is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System(FSMARS), is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.

  8. Semantic Keys and Reading

    Directory of Open Access Journals (Sweden)

    Zev bar-Lev

    2016-12-01

    Full Text Available Semantic Keys are elements (word-parts of written language that give an iconic, general representation of the whole word’s meaning. In written Sino-Japanese the “radical” or semantic components play this role. For example, the character meaning ‘woman, female’ is the Semantic Key of the character for Ma ‘Mama’ (alongside the phonetic component Ma, which means ‘horse’ as a separate character. The theory of semantic Keys in both graphic and phonemic aspects is called qTheory or nanosemantics. The most innovative aspect of the present article is the hypothesis that, in languages using alphabetic writing systems, the role of Semantic Key is played by consonants, more specifically the first consonant. Thus, L meaning ‘LIFT’ is the Semantic Key of English Lift, Ladle, Lofty, aLps, eLevator, oLympus; Spanish Leva, Lecantarse, aLto, Lengua; Arabic aLLah, and Hebrew① ªeL-ºaL ‘upto-above’ (the Israeli airline, Polish Lot ‘flight’ (the Polish airline; Hebrew ªeL, ªeLohim ‘God’, and haLLeluyah ‘praise-ye God’ (using Parallels, ‘Lift up God’. Evidence for the universality of the theory is shown by many examples drawn from various languages, including Indo-European Semitic, Chinese and Japanese. The theory reveals hundreds of relationships within and between languages, related and unrelated, that have been “Hiding in Plain Sight”, to mention just one example: the Parallel between Spanish Pan ‘bread’ and Mandarin Fan ‘rice’.

  9. Impact of Semantic Relatedness on Associative Memory: An ERP Study

    Directory of Open Access Journals (Sweden)

    Pierre Desaunay

    2017-06-01

    Full Text Available Encoding and retrieval processes in memory for pairs of pictures are thought to be influenced by inter-item similarity and by features of individual items. Using Event-Related Potentials (ERP, we aimed to identify how these processes impact on both the early mid-frontal FN400 and the Late Positive Component (LPC potentials during associative retrieval of pictures. Twenty young adults undertook a sham task, using an incidental encoding of semantically related and unrelated pairs of drawings. At test, we conducted a recognition task in which participants were asked to identify target identical pairs of pictures, which could be semantically related or unrelated, among new and rearranged pairs. We observed semantic (related and unrelated pairs and condition effects (old, rearranged and new pairs on the early mid-frontal potential. First, a lower amplitude was shown for identical and rearranged semantically related pairs, which might reflect a retrieval process driven by semantic cues. Second, among semantically unrelated pairs, we found a larger negativity for identical pairs, compared to rearranged and new ones, suggesting additional retrieval processing that focuses on associative information. We also observed an LPC old/new effect with a mid-parietal and a right occipito-parietal topography for semantically related and unrelated old pairs, demonstrating a recollection phenomenon irrespective of the degree of association. These findings suggest that associative recognition using visual stimuli begins at early stages of retrieval, and differs according to the degree of semantic relatedness among items. However, either strategy may ultimately lead to recollection processes.

  10. SEPHYRES 1: A Symptom Checker based on Semantic Pain Descriptors and Weight Spreading

    Directory of Open Access Journals (Sweden)

    Ali SANAEIFAR

    2016-12-01

    Full Text Available Semantic-enabled medical diagnostic systems, which have exploited an ontology in their internal engines, have failed to perfectly describe disease profiles, especially in complex medical terms having a variant generality level or certainty in the medical literature. The main objective of this paper was to present an ontology with a highly matching grade of proeminent medical concepts able to analyze the patient’s descriptive medical condition. Focusing on semantic pain descriptors and weight spreading techniques, we proposed a semantic-pseudo-fuzzy engine entitled SEPHYRES, with which we tried to present an ontology-based solution using not only a generic semantic reasoner but also complementary domain-heuristic reasoning. Having applied the valid evidence-based references along with local experts, we illustrated how the resilient expressive model represents the complex medical term relations. The twenty test cases were extracted from the MEDSCAPE and PubMed databases and the precision and recall were calculated. Finally, the results were compared against the Isabel symptom checker and performed the Wilcoxon signed-rank test. The recall measures indicated that the accuracy was equal to 75%, if the system was adjusted to only ten results as differential diagnoses. Moreover, the Wilcoxon signed-rank test showed that there was significant difference between SEPHYRES and Isabel symptom checker (P= 0.016 so that this method is sufficiently able to improve semantic expressiveness in both professional medical diagnosis and patient decision aid systems.

  11. Relating UMLS semantic types and task-based ontology to computer-interpretable clinical practice guidelines.

    Science.gov (United States)

    Kumar, Anand; Ciccarese, Paolo; Quaglini, Silvana; Stefanelli, Mario; Caffi, Ezio; Boiocchi, Lorenzo

    2003-01-01

    Medical knowledge in clinical practice guideline (GL) texts is the source of task-based computer-interpretable clinical guideline models (CIGMs). We have used Unified Medical Language System (UMLS) semantic types (STs) to understand the percentage of GL text which belongs to a particular ST. We also use UMLS semantic network together with the CIGM-specific ontology to derive a semantic meaning behind the GL text. In order to achieve this objective, we took nine GL texts from the National Guideline Clearinghouse (NGC) and marked up the text dealing with a particular ST. The STs we took into consideration were restricted taking into account the requirements of a task-based CIGM. We used DARPA Agent Markup Language and Ontology Inference Layer (DAML + OIL) to create the UMLS and CIGM specific semantic network. For the latter, as a bench test, we used the 1999 WHO-International Society of Hypertension Guidelines for the Management of Hypertension. We took into consideration the UMLS STs closest to the clinical tasks. The percentage of the GL text dealing with the ST "Health Care Activity" and subtypes "Laboratory Procedure", "Diagnostic Procedure" and "Therapeutic or Preventive Procedure" were measured. The parts of text belonging to other STs or comments were separated. A mapping of terms belonging to other STs was done to the STs under "HCA" for representation in DAML + OIL. As a result, we found that the three STs under "HCA" were the predominant STs present in the GL text. In cases where the terms of related STs existed, they were mapped into one of the three STs. The DAML + OIL representation was able to describe the hierarchy in task-based CIGMs. To conclude, we understood that the three STs could be used to represent the semantic network of the task-bases CIGMs. We identified some mapping operators which could be used for the mapping of other STs into these.

  12. EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness.

    Science.gov (United States)

    Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

    2015-07-14

    Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly "domain general" conflict processing mechanisms, instead of conflict source specific effects.

  13. EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness

    Science.gov (United States)

    Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

    2015-01-01

    Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly “domain general” conflict processing mechanisms, instead of conflict source specific effects. PMID:26169473

  14. Semantic Priming for Coordinate Distant Concepts in Alzheimer's Disease Patients

    Science.gov (United States)

    Perri, R.; Zannino, G. D.; Caltagirone, C.; Carlesimo, G. A.

    2011-01-01

    Semantic priming paradigms have been used to investigate semantic knowledge in patients with Alzheimer's disease (AD). While priming effects produced by prime-target pairs with associative relatedness reflect processes at both lexical and semantic levels, priming effects produced by words that are semantically related but not associated should…

  15. Semantic Multimedia

    NARCIS (Netherlands)

    S. Staab; A. Scherp; R. Arndt; R. Troncy (Raphael); M. Grzegorzek; C. Saathoff; S. Schenk; L. Hardman (Lynda)

    2008-01-01

    htmlabstractMultimedia constitutes an interesting field of application for Semantic Web and Semantic Web reasoning, as the access and management of multimedia content and context depends strongly on the semantic descriptions of both. At the same time, multimedia resources constitute complex objects,

  16. Integrating semantic dimension into openEHR archetypes for the management of cerebral palsy electronic medical records.

    Science.gov (United States)

    Ellouze, Afef Samet; Bouaziz, Rafik; Ghorbel, Hanen

    2016-10-01

    Integrating semantic dimension into clinical archetypes is necessary once modeling medical records. First, it enables semantic interoperability and, it offers applying semantic activities on clinical data and provides a higher design quality of Electronic Medical Record (EMR) systems. However, to obtain these advantages, designers need to use archetypes that cover semantic features of clinical concepts involved in their specific applications. In fact, most of archetypes filed within open repositories are expressed in the Archetype Definition Language (ALD) which allows defining only the syntactic structure of clinical concepts weakening semantic activities on the EMR content in the semantic web environment. This paper focuses on the modeling of an EMR prototype for infants affected by Cerebral Palsy (CP), using the dual model approach and integrating semantic web technologies. Such a modeling provides a better delivery of quality of care and ensures semantic interoperability between all involved therapies' information systems. First, data to be documented are identified and collected from the involved therapies. Subsequently, data are analyzed and arranged into archetypes expressed in accordance of ADL. During this step, open archetype repositories are explored, in order to find the suitable archetypes. Then, ADL archetypes are transformed into archetypes expressed in OWL-DL (Ontology Web Language - Description Language). Finally, we construct an ontological source related to these archetypes enabling hence their annotation to facilitate data extraction and providing possibility to exercise semantic activities on such archetypes. Semantic dimension integration into EMR modeled in accordance to the archetype approach. The feasibility of our solution is shown through the development of a prototype, baptized "CP-SMS", which ensures semantic exploitation of CP EMR. This prototype provides the following features: (i) creation of CP EMR instances and their checking by

  17. Rewriting Logic Semantics of a Plan Execution Language

    Science.gov (United States)

    Dowek, Gilles; Munoz, Cesar A.; Rocha, Camilo

    2009-01-01

    The Plan Execution Interchange Language (PLEXIL) is a synchronous language developed by NASA to support autonomous spacecraft operations. In this paper, we propose a rewriting logic semantics of PLEXIL in Maude, a high-performance logical engine. The rewriting logic semantics is by itself a formal interpreter of the language and can be used as a semantic benchmark for the implementation of PLEXIL executives. The implementation in Maude has the additional benefit of making available to PLEXIL designers and developers all the formal analysis and verification tools provided by Maude. The formalization of the PLEXIL semantics in rewriting logic poses an interesting challenge due to the synchronous nature of the language and the prioritized rules defining its semantics. To overcome this difficulty, we propose a general procedure for simulating synchronous set relations in rewriting logic that is sound and, for deterministic relations, complete. We also report on the finding of two issues at the design level of the original PLEXIL semantics that were identified with the help of the executable specification in Maude.

  18. Relative Weighting of Semantic and Syntactic Cues in Native and Non-Native Listeners' Recognition of English Sentences.

    Science.gov (United States)

    Shi, Lu-Feng; Koenig, Laura L

    2016-01-01

    Non-native listeners do not recognize English sentences as effectively as native listeners, especially in noise. It is not entirely clear to what extent such group differences arise from differences in relative weight of semantic versus syntactic cues. This study quantified the use and weighting of these contextual cues via Boothroyd and Nittrouer's j and k factors. The j represents the probability of recognizing sentences with or without context, whereas the k represents the degree to which context improves recognition performance. Four groups of 13 normal-hearing young adult listeners participated. One group consisted of native English monolingual (EMN) listeners, whereas the other three consisted of non-native listeners contrasting in their language dominance and first language: English-dominant Russian-English, Russian-dominant Russian-English, and Spanish-dominant Spanish-English bilinguals. All listeners were presented three sets of four-word sentences: high-predictability sentences included both semantic and syntactic cues, low-predictability sentences included syntactic cues only, and zero-predictability sentences included neither semantic nor syntactic cues. Sentences were presented at 65 dB SPL binaurally in the presence of speech-spectrum noise at +3 dB SNR. Listeners orally repeated each sentence and recognition was calculated for individual words as well as the sentence as a whole. Comparable j values across groups for high-predictability, low-predictability, and zero-predictability sentences suggested that all listeners, native and non-native, utilized contextual cues to recognize English sentences. Analysis of the k factor indicated that non-native listeners took advantage of syntax as effectively as EMN listeners. However, only English-dominant bilinguals utilized semantics to the same extent as EMN listeners; semantics did not provide a significant benefit for the two non-English-dominant groups. When combined, semantics and syntax benefitted EMN

  19. Semantic transparency, semantic opacity, states of affairs, mental states and speech acts

    OpenAIRE

    Reboul , Anne

    2001-01-01

    There are two well-known views of linguistic communication: the code model and its counterpart, the hypothesis of the semantic transparency. If both of these views were correct, then there would be only one possible type of mishap in communication, that due to noise in the communication channel. However, none of these views is correct. I will sketch a quick history of pragmatics relative both to the code model and to the hypothesis of semantic transparency. As we will see, the most recent pra...

  20. SEMSIN SEMANTIC AND SYNTACTIC PARSER

    Directory of Open Access Journals (Sweden)

    K. K. Boyarsky

    2015-09-01

    Full Text Available The paper deals with the principle of operation for SemSin semantic and syntactic parser creating a dependency tree for the Russian language sentences. The parser consists of 4 blocks: a dictionary, morphological analyzer, production rules and lexical analyzer. An important logical part of the parser is pre-syntactical module, which harmonizes and complements morphological analysis results, separates the text paragraphs into individual sentences, and also carries out predisambiguation. Characteristic feature of the presented parser is an open type of control – it is done by means of a set of production rules. A varied set of commands provides the ability to both morphological and semantic-syntactic analysis of the sentence. The paper presents the sequence of rules usage and examples of their work. Specific feature of the rules is the decision making on establishment of syntactic links with simultaneous removal of the morphological and semantic ambiguity. The lexical analyzer provides the execution of commands and rules, and manages the parser in manual or automatic modes of the text analysis. In the first case, the analysis is performed interactively with the possibility of step-by-step execution of the rules and scanning the resulting parse tree. In the second case, analysis results are filed in an xml-file. Active usage of syntactic and semantic dictionary information gives the possibility to reduce significantly the ambiguity of parsing. In addition to marking the text, the parser is also usable as a tool for information extraction from natural language texts.

  1. Compiling Dictionaries Using Semantic Domains*

    Directory of Open Access Journals (Sweden)

    Ronald Moe

    2011-10-01

    Full Text Available

    Abstract: The task of providing dictionaries for all the world's languages is prodigious, re-quiring efficient techniques. The text corpus method cannot be used for minority languages lacking texts. To meet the need, the author has constructed a list of 1 600 semantic domains, which he has successfully used to collect words. In a workshop setting, a group of speakers can collect as many as 17 000 words in ten days. This method results in a classified word list that can be efficiently expanded into a full dictionary. The method works because the mental lexicon is a giant web or-ganized around key concepts. A semantic domain can be defined as an important concept together with the words directly related to it by lexical relations. A person can utilize the mental web to quickly jump from word to word within a domain. The author is developing a template for each domain to aid in collecting words and in de-scribing their semantics. Investigating semantics within the context of a domain yields many in-sights. The method permits the production of both alphabetically and semantically organized dic-tionaries. The list of domains is intended to be universal in scope and applicability. Perhaps due to universals of human experience and universals of linguistic competence, there are striking simi-larities in various lists of semantic domains developed for languages around the world. Using a standardized list of domains to classify multiple dictionaries opens up possibilities for cross-lin-guistic research into semantic and lexical universals.

    Keywords: SEMANTIC DOMAINS, SEMANTIC FIELDS, SEMANTIC CATEGORIES, LEX-ICAL RELATIONS, SEMANTIC PRIMITIVES, DOMAIN TEMPLATES, MENTAL LEXICON, SEMANTIC UNIVERSALS, MINORITY LANGUAGES, LEXICOGRAPHY

    Opsomming: Samestelling van woordeboeke deur gebruikmaking van se-mantiese domeine. Die taak van die voorsiening van woordeboeke aan al die tale van die wêreld is geweldig en vereis doeltreffende tegnieke. Die

  2. Activation of semantic information at the sublexical level during handwriting production: Evidence from inhibition effects of Chinese semantic radicals in the picture-word interference paradigm.

    Science.gov (United States)

    Chen, Xuqian; Liao, Yuanlan; Chen, Xianzhe

    2017-08-01

    Using a non-alphabetic language (e.g., Chinese), the present study tested a novel view that semantic information at the sublexical level should be activated during handwriting production. Over 80% of Chinese characters are phonograms, in which semantic radicals represent category information (e.g., 'chair,' 'peach,' 'orange' are related to plants) while phonetic radicals represent phonetic information (e.g., 'wolf,' 'brightness,' 'male,' are all pronounced /lang/). Under different semantic category conditions at the lexical level (semantically related in Experiment 1; semantically unrelated in Experiment 2), the orthographic relatedness and semantic relatedness of semantic radicals in the picture name and its distractor were manipulated under different SOAs (i.e., stimulus onset asynchrony, the interval between the onset of the picture and the onset of the interference word). Two questions were addressed: (1) Is it possible that semantic information could be activated in the sublexical level conditions? (2) How are semantic and orthographic information dynamically accessed in word production? Results showed that both orthographic and semantic information were activated under the present picture-word interference paradigm, dynamically under different SOAs, which supported our view that discussions on semantic processes in the writing modality should be extended to the sublexical level. The current findings provide possibility for building new orthography-phonology-semantics models in writing. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  3. Enabling Semantic Queries Against the Spatial Database

    Directory of Open Access Journals (Sweden)

    PENG, X.

    2012-02-01

    Full Text Available The spatial database based upon the object-relational database management system (ORDBMS has the merits of a clear data model, good operability and high query efficiency. That is why it has been widely used in spatial data organization and management. However, it cannot express the semantic relationships among geospatial objects, making the query results difficult to meet the user's requirement well. Therefore, this paper represents an attempt to combine the Semantic Web technology with the spatial database so as to make up for the traditional database's disadvantages. In this way, on the one hand, users can take advantages of ORDBMS to store and manage spatial data; on the other hand, if the spatial database is released in the form of Semantic Web, the users could describe a query more concisely with the cognitive pattern which is similar to that of daily life. As a consequence, this methodology enables the benefits of both Semantic Web and the object-relational database (ORDB available. The paper discusses systematically the semantic enriched spatial database's architecture, key technologies and implementation. Subsequently, we demonstrate the function of spatial semantic queries via a practical prototype system. The query results indicate that the method used in this study is feasible.

  4. Semantic attributes based texture generation

    Science.gov (United States)

    Chi, Huifang; Gan, Yanhai; Qi, Lin; Dong, Junyu; Madessa, Amanuel Hirpa

    2018-04-01

    Semantic attributes are commonly used for texture description. They can be used to describe the information of a texture, such as patterns, textons, distributions, brightness, and so on. Generally speaking, semantic attributes are more concrete descriptors than perceptual features. Therefore, it is practical to generate texture images from semantic attributes. In this paper, we propose to generate high-quality texture images from semantic attributes. Over the last two decades, several works have been done on texture synthesis and generation. Most of them focusing on example-based texture synthesis and procedural texture generation. Semantic attributes based texture generation still deserves more devotion. Gan et al. proposed a useful joint model for perception driven texture generation. However, perceptual features are nonobjective spatial statistics used by humans to distinguish different textures in pre-attentive situations. To give more describing information about texture appearance, semantic attributes which are more in line with human description habits are desired. In this paper, we use sigmoid cross entropy loss in an auxiliary model to provide enough information for a generator. Consequently, the discriminator is released from the relatively intractable mission of figuring out the joint distribution of condition vectors and samples. To demonstrate the validity of our method, we compare our method to Gan et al.'s method on generating textures by designing experiments on PTD and DTD. All experimental results show that our model can generate textures from semantic attributes.

  5. Integrated use of spatial and semantic relationships for extracting road networks from floating car data

    Science.gov (United States)

    Li, Jun; Qin, Qiming; Xie, Chao; Zhao, Yue

    2012-10-01

    The update frequency of digital road maps influences the quality of road-dependent services. However, digital road maps surveyed by probe vehicles or extracted from remotely sensed images still have a long updating circle and their cost remain high. With GPS technology and wireless communication technology maturing and their cost decreasing, floating car technology has been used in traffic monitoring and management, and the dynamic positioning data from floating cars become a new data source for updating road maps. In this paper, we aim to update digital road maps using the floating car data from China's National Commercial Vehicle Monitoring Platform, and present an incremental road network extraction method suitable for the platform's GPS data whose sampling frequency is low and which cover a large area. Based on both spatial and semantic relationships between a trajectory point and its associated road segment, the method classifies each trajectory point, and then merges every trajectory point into the candidate road network through the adding or modifying process according to its type. The road network is gradually updated until all trajectories have been processed. Finally, this method is applied in the updating process of major roads in North China and the experimental results reveal that it can accurately derive geometric information of roads under various scenes. This paper provides a highly-efficient, low-cost approach to update digital road maps.

  6. Knowledge representation and management: benefits and challenges of the semantic web for the fields of KRM and NLP.

    Science.gov (United States)

    Rassinoux, A-M

    2011-01-01

    To summarize excellent current research in the field of knowledge representation and management (KRM). A synopsis of the articles selected for the IMIA Yearbook 2011 is provided and an attempt to highlight the current trends in the field is sketched. This last decade, with the extension of the text-based web towards a semantic-structured web, NLP techniques have experienced a renewed interest in knowledge extraction. This trend is corroborated through the five papers selected for the KRM section of the Yearbook 2011. They all depict outstanding studies that exploit NLP technologies whenever possible in order to accurately extract meaningful information from various biomedical textual sources. Bringing semantic structure to the meaningful content of textual web pages affords the user with cooperative sharing and intelligent finding of electronic data. As exemplified by the best paper selection, more and more advanced biomedical applications aim at exploiting the meaningful richness of free-text documents in order to generate semantic metadata and recently to learn and populate domain ontologies. These later are becoming a key piece as they allow portraying the semantics of the Semantic Web content. Maintaining their consistency with documents and semantic annotations that refer to them is a crucial challenge of the Semantic Web for the coming years.

  7. A JBI Information Object Engineering Environment Utilizing Metadata Fragments for Refining Searches on Semantically-Related Object Types

    National Research Council Canada - National Science Library

    Harlow, Felicia N

    2005-01-01

    .... This enhancement will improve the ability of JBI users to create and store IO type schemas, and query and subscribe to information objects, which may be semantically related by their inclusion...

  8. Semantic matchmaking with nonmonotonic description logics

    CERN Document Server

    Grimm, S

    2009-01-01

    Semantic web has grown into a mature field of research. Its methods find innovative applications on and off the World Wide Web. Its underlying technologies have significant impact on adjacent fields of research and on industrial applications. This new book series reports on the state-of-the-art in foundations, methods, and applications of semantic web and its underlying technologies. It is a central forum for the communication of recent developments and comprises research monographs, textbooks and edited volumes on all topics related to the semantic web. In this first volume several non-monoto

  9. Semantic and syntactic interoperability in online processing of big Earth observation data.

    Science.gov (United States)

    Sudmanns, Martin; Tiede, Dirk; Lang, Stefan; Baraldi, Andrea

    2018-01-01

    The challenge of enabling syntactic and semantic interoperability for comprehensive and reproducible online processing of big Earth observation (EO) data is still unsolved. Supporting both types of interoperability is one of the requirements to efficiently extract valuable information from the large amount of available multi-temporal gridded data sets. The proposed system wraps world models, (semantic interoperability) into OGC Web Processing Services (syntactic interoperability) for semantic online analyses. World models describe spatio-temporal entities and their relationships in a formal way. The proposed system serves as enabler for (1) technical interoperability using a standardised interface to be used by all types of clients and (2) allowing experts from different domains to develop complex analyses together as collaborative effort. Users are connecting the world models online to the data, which are maintained in a centralised storage as 3D spatio-temporal data cubes. It allows also non-experts to extract valuable information from EO data because data management, low-level interactions or specific software issues can be ignored. We discuss the concept of the proposed system, provide a technical implementation example and describe three use cases for extracting changes from EO images and demonstrate the usability also for non-EO, gridded, multi-temporal data sets (CORINE land cover).

  10. The Semantics of "Violence"

    DEFF Research Database (Denmark)

    Levisen, Carsten

    This paper presents a semantic analysis of “violence” – a word around which Anglo-internationaldiscourses revolve. Many ethnolinguistic communities around the world are currently adapting thisEnglish lexical concept into their linguistic systems, and, presumably also, the view of the worldembodied...... by the “violence” concept.Based on semantic fieldwork in Port Vila, the creolophone capital of Vanuatu in the SouthPacific, the paper investigates the discursive introduction of “violence” into a community which,until recently, lived by other concepts. I compare and contrast the traditional Bislama concepts...... kilimand faetem with the newly imported English word vaeolens (violence). My study provides newevidence for how cognitive and semantic change co-occur in the context of postcolonial linguisticcommunities, and my paper addresses an important, ongoing controversy related to the notion of“Anglocentric bias...

  11. Weakly supervised semantic segmentation using fore-background priors

    Science.gov (United States)

    Han, Zheng; Xiao, Zhitao; Yu, Mingjun

    2017-07-01

    Weakly-supervised semantic segmentation is a challenge in the field of computer vision. Most previous works utilize the labels of the whole training set and thereby need the construction of a relationship graph about image labels, thus result in expensive computation. In this study, we tackle this problem from a different perspective. We proposed a novel semantic segmentation algorithm based on background priors, which avoids the construction of a huge graph in whole training dataset. Specifically, a random forest classifier is obtained using weakly supervised training data .Then semantic texton forest (STF) feature is extracted from image superpixels. Finally, a CRF based optimization algorithm is proposed. The unary potential of CRF derived from the outputting probability of random forest classifier and the robust saliency map as background prior. Experiments on the MSRC21 dataset show that the new algorithm outperforms some previous influential weakly-supervised segmentation algorithms. Furthermore, the use of efficient decision forests classifier and parallel computing of saliency map significantly accelerates the implementation.

  12. Towards Semantic Understanding of Surrounding Vehicular Maneuvers

    DEFF Research Database (Denmark)

    Kristoffersen, Miklas Strøm; Dueholm, Jacob Velling; Satzoda, Ravi K.

    2016-01-01

    This paper proposes the use of multiple low-cost visual sensors to obtain a surround view of the ego-vehicle for semantic understanding. A multi-perspective view will assist the analysis of naturalistic driving studies (NDS), by automating the task of data reduction of the observed sequences...... into events. A user-centric vision-based framework is presented using a vehicle detector and tracker in each separate perspective. Multi-perspective trajectories are estimated and analyzed to extract 14 different events, including potential dangerous behaviors such as overtakes and cut-ins. The system...... is tested on ten sequences of real-world data collected on U. S. highways. The results show the potential use of multiple low-cost visual sensors for semantic understanding around the ego-vehicle....

  13. Tweets clustering using latent semantic analysis

    Science.gov (United States)

    Rasidi, Norsuhaili Mahamed; Bakar, Sakhinah Abu; Razak, Fatimah Abdul

    2017-04-01

    Social media are becoming overloaded with information due to the increasing number of information feeds. Unlike other social media, Twitter users are allowed to broadcast a short message called as `tweet". In this study, we extract tweets related to MH370 for certain of time. In this paper, we present overview of our approach for tweets clustering to analyze the users' responses toward tragedy of MH370. The tweets were clustered based on the frequency of terms obtained from the classification process. The method we used for the text classification is Latent Semantic Analysis. As a result, there are two types of tweets that response to MH370 tragedy which is emotional and non-emotional. We show some of our initial results to demonstrate the effectiveness of our approach.

  14. Generative Semantics.

    Science.gov (United States)

    King, Margaret

    The first section of this paper deals with the attempts within the framework of transformational grammar to make semantics a systematic part of linguistic description, and outlines the characteristics of the generative semantics position. The second section takes a critical look at generative semantics in its later manifestations, and makes a case…

  15. Semantic processes leading to true and false memory formation in schizophrenia.

    Science.gov (United States)

    Paz-Alonso, Pedro M; Ghetti, Simona; Ramsay, Ian; Solomon, Marjorie; Yoon, Jong; Carter, Cameron S; Ragland, J Daniel

    2013-07-01

    Encoding semantic relationships between items on word lists (semantic processing) enhances true memories, but also increases memory distortions. Episodic memory impairments in schizophrenia (SZ) are strongly driven by failures to process semantic relations, but the exact nature of these relational semantic processing deficits is not well understood. Here, we used a false memory paradigm to investigate the impact of implicit and explicit semantic processing manipulations on episodic memory in SZ. Thirty SZ and 30 demographically matched healthy controls (HC) studied Deese/Roediger-McDermott (DRM) lists of semantically associated words. Half of the lists had strong implicit semantic associations and the remainder had low strength associations. Similarly, half of the lists were presented under "standard" instructions and the other half under explicit "relational processing" instructions. After study, participants performed recall and old/new recognition tests composed of targets, critical lures, and unrelated lures. HC exhibited higher true memories and better discriminability between true and false memory compared to SZ. High, versus low, associative strength increased false memory rates in both groups. However, explicit "relational processing" instructions positively improved true memory rates only in HC. Finally, true and false memory rates were associated with severity of disorganized and negative symptoms in SZ. These results suggest that reduced processing of semantic relationships during encoding in SZ may stem from an inability to implement explicit relational processing strategies rather than a fundamental deficit in the implicit activation and retrieval of word meanings from patients' semantic lexicon. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. Visuospatial working memory in children with autism: the effect of a semantic global organization.

    Science.gov (United States)

    Mammarella, Irene C; Giofrè, David; Caviola, Sara; Cornoldi, Cesare; Hamilton, Colin

    2014-06-01

    It has been reported that individuals with Autism Spectrum Disorders (ASD) perceive visual scenes as a sparse set of details rather than as a congruent and meaningful unit, failing in the extraction of the global configuration of the scene. In the present study, children with ASD were compared with typically developing (TD) children, in a visuospatial working memory task, the Visual Patterns Test (VPT). The VPT array was manipulated to vary the semantic affordance of the pattern, high semantic (global) vs. low semantic; temporal parameters were also manipulated within the change detection protocol. Overall, there was no main effect associated with Group, however there was a significant effect associated with Semantics, which was further qualified by an interaction between the Group and Semantic factors; there was only a significant effect of semantics in the TD group. The findings are discussed in light of the weak central coherence theory where the ASD group are unable to make use of long term memory semantics in order to construct global representations of the array. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Self-referential processing is distinct from semantic elaboration: evidence from long-term memory effects in a patient with amnesia and semantic impairments.

    Science.gov (United States)

    Sui, Jie; Humphreys, Glyn W

    2013-11-01

    We report data demonstrating that self-referential encoding facilitates memory performance in the absence of effects of semantic elaboration in a severely amnesic patient also suffering semantic problems. In Part 1, the patient, GA, was trained to associate items with the self or a familiar other during the encoding phase of a memory task (self-ownership decisions in Experiment 1 and self-evaluation decisions in Experiment 2). Tests of memory showed a consistent self-reference advantage, relative to a condition where the reference was another person in both experiments. The pattern of the self-reference advantage was similar to that in healthy controls. In Part 2 we demonstrate that GA showed minimal effects of semantic elaboration on memory for items he semantically classified, compared with items subject to physical size decisions; in contrast, healthy controls demonstrated enhanced memory performance after semantic relative to physical encoding. The results indicate that self-referential encoding, not semantic elaboration, improves memory in amnesia. Self-referential processing may provide a unique scaffold to help improve learning in amnesic cases. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Relationship Structures and Semantic Type Assignments of the UMLS Enriched Semantic Network

    Science.gov (United States)

    Zhang, Li; Halper, Michael; Perl, Yehoshua; Geller, James; Cimino, James J.

    2005-01-01

    Objective: The Enriched Semantic Network (ESN) was introduced as an extension of the Unified Medical Language System (UMLS) Semantic Network (SN). Its multiple subsumption configuration and concomitant multiple inheritance make the ESN's relationship structures and semantic type assignments different from those of the SN. A technique for deriving the relationship structures of the ESN's semantic types and an automated technique for deriving the ESN's semantic type assignments from those of the SN are presented. Design: The technique to derive the ESN's relationship structures finds all newly inherited relationships in the ESN. All such relationships are audited for semantic validity, and the blocking mechanism is used to block invalid relationships. The mapping technique to derive the ESN's semantic type assignments uses current SN semantic type assignments and preserves nonredundant categorizations, while preventing new redundant categorizations. Results: Among the 426 newly inherited relationships, 326 are deemed valid. Seven blockings are applied to avoid inheritance of the 100 invalid relationships. Sixteen semantic types have different relationship structures in the ESN as compared to those in the SN. The mapping of semantic type assignments from the SN to the ESN avoids the generation of 26,950 redundant categorizations. The resulting ESN contains 138 semantic types, 149 IS-A links, 7,303 relationships, and 1,013,876 semantic type assignments. Conclusion: The ESN's multiple inheritance provides more complete relationship structures than in the SN. The ESN's semantic type assignments avoid the existing redundant categorizations appearing in the SN and prevent new ones that might arise due to multiple parents. Compared to the SN, the ESN provides a more accurate unifying semantic abstraction of the UMLS Metathesaurus. PMID:16049233

  19. Acoustic and semantic interference effects in words and pictures.

    Science.gov (United States)

    Dhawan, M; Pellegrino, J W

    1977-05-01

    Interference effects for pictures and words were investigated using a probe-recall task. Word stimuli showed acoustic interference effects for items at the end of the list and semantic interference effects for items at the beginning of the list, similar to results of Kintsch and Buschke (1969). Picture stimuli showed large semantic interference effects at all list positions with smaller acoustic interference effects. The results were related to latency data on picture-word processing and interpreted in terms of the differential order, probability, and/or speed of access to acoustic and semantic levels of processing. A levels of processing explanation of picture-word retention differences was related to dual coding theory. Both theoretical positions converge on an explanation of picture-word retention differences as a function of the relative capacity for semantic or associative processing.

  20. Hybrid Semantic Analysis for Mapping Adverse Drug Reaction Mentions in Tweets to Medical Terminology.

    Science.gov (United States)

    Emadzadeh, Ehsan; Sarker, Abeed; Nikfarjam, Azadeh; Gonzalez, Graciela

    2017-01-01

    Social networks, such as Twitter, have become important sources for active monitoring of user-reported adverse drug reactions (ADRs). Automatic extraction of ADR information can be crucial for healthcare providers, drug manufacturers, and consumers. However, because of the non-standard nature of social media language, automatically extracted ADR mentions need to be mapped to standard forms before they can be used by operational pharmacovigilance systems. We propose a modular natural language processing pipeline for mapping (normalizing) colloquial mentions of ADRs to their corresponding standardized identifiers. We seek to accomplish this task and enable customization of the pipeline so that distinct unlabeled free text resources can be incorporated to use the system for other normalization tasks. Our approach, which we call Hybrid Semantic Analysis (HSA), sequentially employs rule-based and semantic matching algorithms for mapping user-generated mentions to concept IDs in the Unified Medical Language System vocabulary. The semantic matching component of HSA is adaptive in nature and uses a regression model to combine various measures of semantic relatedness and resources to optimize normalization performance on the selected data source. On a publicly available corpus, our normalization method achieves 0.502 recall and 0.823 precision (F-measure: 0.624). Our proposed method outperforms a baseline based on latent semantic analysis and another that uses MetaMap.

  1. Trust estimation of the semantic web using semantic web clustering

    Science.gov (United States)

    Shirgahi, Hossein; Mohsenzadeh, Mehran; Haj Seyyed Javadi, Hamid

    2017-05-01

    Development of semantic web and social network is undeniable in the Internet world these days. Widespread nature of semantic web has been very challenging to assess the trust in this field. In recent years, extensive researches have been done to estimate the trust of semantic web. Since trust of semantic web is a multidimensional problem, in this paper, we used parameters of social network authority, the value of pages links authority and semantic authority to assess the trust. Due to the large space of semantic network, we considered the problem scope to the clusters of semantic subnetworks and obtained the trust of each cluster elements as local and calculated the trust of outside resources according to their local trusts and trust of clusters to each other. According to the experimental result, the proposed method shows more than 79% Fscore that is about 11.9% in average more than Eigen, Tidal and centralised trust methods. Mean of error in this proposed method is 12.936, that is 9.75% in average less than Eigen and Tidal trust methods.

  2. Semantic computing and language knowledge bases

    Science.gov (United States)

    Wang, Lei; Wang, Houfeng; Yu, Shiwen

    2017-09-01

    As the proposition of the next-generation Web - semantic Web, semantic computing has been drawing more and more attention within the circle and the industries. A lot of research has been conducted on the theory and methodology of the subject, and potential applications have also been investigated and proposed in many fields. The progress of semantic computing made so far cannot be detached from its supporting pivot - language resources, for instance, language knowledge bases. This paper proposes three perspectives of semantic computing from a macro view and describes the current status of affairs about the construction of language knowledge bases and the related research and applications that have been carried out on the basis of these resources via a case study in the Institute of Computational Linguistics at Peking University.

  3. The neural mechanisms of semantic and response conflicts: an fMRI study of practice-related effects in the Stroop task.

    Science.gov (United States)

    Chen, Zhencai; Lei, Xu; Ding, Cody; Li, Hong; Chen, Antao

    2013-02-01

    Previous studies have demonstrated that there are separate neural mechanisms underlying semantic and response conflicts in the Stroop task. However, the practice effects of these conflicts need to be elucidated and the possible involvements of common neural mechanisms are yet to be established. We employed functional magnetic resonance imaging (fMRI) in a 4-2 mapping practice-related Stroop task to determine the neural substrates under these conflicts. Results showed that different patterns of brain activations are associated with practice in the attentional networks (e.g., dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and posterior parietal cortex (PPC)) for both conflicts, response control regions (e.g., inferior frontal junction (IFJ), inferior frontal gyrus (IFG)/insula, and pre-supplementary motor areas (pre-SMA)) for semantic conflict, and posterior cortex for response conflict. We also found areas of common activation in the left hemisphere within the attentional networks, for the early practice stage in semantic conflict and the late stage in "pure" response conflict using conjunction analysis. The different practice effects indicate that there are distinct mechanisms underlying these two conflict types: semantic conflict practice effects are attributable to the automation of stimulus processing, conflict and response control; response conflict practice effects are attributable to the proportional increase of conflict-related cognitive resources. In addition, the areas of common activation suggest that the semantic conflict effect may contain a partial response conflict effect, particularly at the beginning of the task. These findings indicate that there are two kinds of response conflicts contained in the key-pressing Stroop task: the vocal-level (mainly in the early stage) and key-pressing (mainly in the late stage) response conflicts; thus, the use of the subtraction method for the exploration of semantic and response conflicts

  4. POLITICAL DISCOURSE – A SYNTACTIC AND SEMANTIC ANALYSIS

    Directory of Open Access Journals (Sweden)

    Miodarka Tepavcevic

    2014-11-01

    Full Text Available The language of politics is commonly studied within discourse analysis, whereby its linguistic features relating to vocabulary, grammar structures, textual and intertextual aspects are investigated using various methodologies. This paper presents an analysis of political discourse from a syntactic-semantic point of view. The corpus studied has been extracted from five. Montenegrin dailies and the analysis attempts to describe the genre as effectuated in the Montenegrin political discourse. As a result, the functions of political language are extrapolated and illustrated and its style is described in terms of intertextuality and other linguistic strategies commonly employed in political discourse. The paper aims to give a contribution to the understanding and linguistic profiling of political language.

  5. Electrocortical N400 Effects of Semantic Satiation

    Directory of Open Access Journals (Sweden)

    Kim Ströberg

    2017-12-01

    Full Text Available Semantic satiation is characterised by the subjective and temporary loss of meaning after high repetition of a prime word. To study the nature of this effect, previous electroencephalography (EEG research recorded the N400, an ERP component that is sensitive to violations of semantic context. The N400 is characterised by a relative negativity to words that are unrelated vs. related to the semantic context. The semantic satiation hypothesis predicts that the N400 should decrease with high repetition. However, previous findings have been inconsistent. Because of these inconsistent findings and the shortcomings of previous research, we used a modified design that minimises confounding effects from non-semantic processes. We recorded 64-channel EEG and analysed the N400 in a semantic priming task in which the primes were repeated 3 or 30 times. Critically, we separated low and high repetition trials and excluded response trials. Further, we varied the physical features (letter case and format of consecutive primes to minimise confounding effects from perceptual habituation. For centrofrontal electrodes, the N400 was reduced after 30 repetitions (vs. 3 repetitions. Explorative source reconstructions suggested that activity decreased after 30 repetitions in bilateral inferior temporal gyrus, the right posterior section of the superior and middle temporal gyrus, right supramarginal gyrus, bilateral lateral occipital cortex, and bilateral lateral orbitofrontal cortex. These areas overlap broadly with those typically involved in the N400, namely middle temporal gyrus and inferior frontal gyrus. The results support the semantic rather than the perceptual nature of the satiation effect.

  6. Flexible recruitment of semantic richness: Context modulates body-object interaction effects in lexical-semantic processing

    Directory of Open Access Journals (Sweden)

    Cody eTousignant

    2012-03-01

    Full Text Available Body-object interaction (BOI is a semantic richness variable that measures the perceived ease with which the human body can physically interact with a word’s referent. Lexical and semantic processing is facilitated when words are associated with relatively more bodily experience (high BOI words, e.g., belt. To date, BOI effects have been examined in only one semantic decision context (is it imageable?. It has been argued that semantic processing is dynamic and can be modulated by context. We examined these influences by testing how task knowledge modulated BOI effects. We presented the same stimuli (high- and low-BOI entity words and a set of action words in each of four action/entity semantic categorization tasks (SCTs. Task framing was manipulated: participants were told about one (actions or entities or both (actions and entities categories of words in the decision task. Facilitatory BOI effects were observed when participants knew that ‘entity’ was part of the decision category, regardless of whether the high- and low-BOI entity words appeared on the affirmative or negative side of the decision. That BOI information was only useful when participants had expectations that object words would be presented suggests a strong role for the decision context in lexical-semantic processing, and supports a dynamic view of conceptual knowledge.

  7. The neural substrates of semantic memory deficits in early Alzheimer's disease: Clues from semantic priming effects and FDG-PET

    Energy Technology Data Exchange (ETDEWEB)

    Giffard, B.; Laisney, M.; Mezenge, F.; De la Sayette, V.; Eustache, F.; Desgranges, B. [Univ Caen Basse Normandie, INSERM, U923, Unite Rech, EPHE, Lab Neuropsychol, CHU Cote Nacre, GIP Cyceron, F-14033 Caen (France)

    2008-07-01

    The neural substrates responsible for semantic dysfunction during the early stages of AD have yet to be clearly identified. After a brief overview of the literature on normal and pathological semantic memory, we describe a new approach, designed to provide fresh insights into semantic deficits in AD. We mapped the correlations between resting-state brain glucose utilisation measured by FDG-PET and semantic priming scores in a group of 17 AD patients. The priming task, which yields a particularly pure measurement of semantic memory, was composed of related pairs of words sharing an attribute relationship (e.g. tiger-stripe). The priming scores correlated positively with the metabolism of the superior temporal areas on both sides, especially the right side, and this correlation was shown to be specific to the semantic priming effect.This pattern of results is discussed in the light of recent theoretical models of semantic memory, and suggests that a dysfunction of the right superior temporal cortex may contribute to early semantic deficits, characterised by the loss of specific features of concepts in AD. (authors)

  8. Processing of visual semantic information to concrete words: temporal dynamics and neural mechanisms indicated by event-related brain potentials( ).

    Science.gov (United States)

    van Schie, Hein T; Wijers, Albertus A; Mars, Rogier B; Benjamins, Jeroen S; Stowe, Laurie A

    2005-05-01

    Event-related brain potentials were used to study the retrieval of visual semantic information to concrete words, and to investigate possible structural overlap between visual object working memory and concreteness effects in word processing. Subjects performed an object working memory task that involved 5 s retention of simple 4-angled polygons (load 1), complex 10-angled polygons (load 2), and a no-load baseline condition. During the polygon retention interval subjects were presented with a lexical decision task to auditory presented concrete (imageable) and abstract (nonimageable) words, and pseudowords. ERP results are consistent with the use of object working memory for the visualisation of concrete words. Our data indicate a two-step processing model of visual semantics in which visual descriptive information of concrete words is first encoded in semantic memory (indicated by an anterior N400 and posterior occipital positivity), and is subsequently visualised via the network for object working memory (reflected by a left frontal positive slow wave and a bilateral occipital slow wave negativity). Results are discussed in the light of contemporary models of semantic memory.

  9. Automatic extraction of property norm-like data from large text corpora.

    Science.gov (United States)

    Kelly, Colin; Devereux, Barry; Korhonen, Anna

    2014-01-01

    Traditional methods for deriving property-based representations of concepts from text have focused on either extracting only a subset of possible relation types, such as hyponymy/hypernymy (e.g., car is-a vehicle) or meronymy/metonymy (e.g., car has wheels), or unspecified relations (e.g., car--petrol). We propose a system for the challenging task of automatic, large-scale acquisition of unconstrained, human-like property norms from large text corpora, and discuss the theoretical implications of such a system. We employ syntactic, semantic, and encyclopedic information to guide our extraction, yielding concept-relation-feature triples (e.g., car be fast, car require petrol, car cause pollution), which approximate property-based conceptual representations. Our novel method extracts candidate triples from parsed corpora (Wikipedia and the British National Corpus) using syntactically and grammatically motivated rules, then reweights triples with a linear combination of their frequency and four statistical metrics. We assess our system output in three ways: lexical comparison with norms derived from human-generated property norm data, direct evaluation by four human judges, and a semantic distance comparison with both WordNet similarity data and human-judged concept similarity ratings. Our system offers a viable and performant method of plausible triple extraction: Our lexical comparison shows comparable performance to the current state-of-the-art, while subsequent evaluations exhibit the human-like character of our generated properties.

  10. A fusion network for semantic segmentation using RGB-D data

    Science.gov (United States)

    Yuan, Jiahui; Zhang, Kun; Xia, Yifan; Qi, Lin; Dong, Junyu

    2018-04-01

    Semantic scene parsing is considerable in many intelligent field, including perceptual robotics. For the past few years, pixel-wise prediction tasks like semantic segmentation with RGB images has been extensively studied and has reached very remarkable parsing levels, thanks to convolutional neural networks (CNNs) and large scene datasets. With the development of stereo cameras and RGBD sensors, it is expected that additional depth information will help improving accuracy. In this paper, we propose a semantic segmentation framework incorporating RGB and complementary depth information. Motivated by the success of fully convolutional networks (FCN) in semantic segmentation field, we design a fully convolutional networks consists of two branches which extract features from both RGB and depth data simultaneously and fuse them as the network goes deeper. Instead of aggregating multiple model, our goal is to utilize RGB data and depth data more effectively in a single model. We evaluate our approach on the NYU-Depth V2 dataset, which consists of 1449 cluttered indoor scenes, and achieve competitive results with the state-of-the-art methods.

  11. Remote semantic memory is impoverished in hippocampal amnesia.

    Science.gov (United States)

    Klooster, Nathaniel B; Duff, Melissa C

    2015-12-01

    The necessity of the hippocampus for acquiring new semantic concepts is a topic of considerable debate. However, it is generally accepted that any role the hippocampus plays in semantic memory is time limited and that previously acquired information becomes independent of the hippocampus over time. This view, along with intact naming and word-definition matching performance in amnesia, has led to the notion that remote semantic memory is intact in patients with hippocampal amnesia. Motivated by perspectives of word learning as a protracted process where additional features and senses of a word are added over time, and by recent discoveries about the time course of hippocampal contributions to on-line relational processing, reconsolidation, and the flexible integration of information, we revisit the notion that remote semantic memory is intact in amnesia. Using measures of semantic richness and vocabulary depth from psycholinguistics and first and second language-learning studies, we examined how much information is associated with previously acquired, highly familiar words in a group of patients with bilateral hippocampal damage and amnesia. Relative to healthy demographically matched comparison participants and a group of brain-damaged comparison participants, the patients with hippocampal amnesia performed significantly worse on both productive and receptive measures of vocabulary depth and semantic richness. These findings suggest that remote semantic memory is impoverished in patients with hippocampal amnesia and that the hippocampus may play a role in the maintenance and updating of semantic memory beyond its initial acquisition. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Applying Semantic Web technologies to improve the retrieval, credibility and use of health-related web resources.

    Science.gov (United States)

    Mayer, Miguel A; Karampiperis, Pythagoras; Kukurikos, Antonis; Karkaletsis, Vangelis; Stamatakis, Kostas; Villarroel, Dagmar; Leis, Angela

    2011-06-01

    The number of health-related websites is increasing day-by-day; however, their quality is variable and difficult to assess. Various "trust marks" and filtering portals have been created in order to assist consumers in retrieving quality medical information. Consumers are using search engines as the main tool to get health information; however, the major problem is that the meaning of the web content is not machine-readable in the sense that computers cannot understand words and sentences as humans can. In addition, trust marks are invisible to search engines, thus limiting their usefulness in practice. During the last five years there have been different attempts to use Semantic Web tools to label health-related web resources to help internet users identify trustworthy resources. This paper discusses how Semantic Web technologies can be applied in practice to generate machine-readable labels and display their content, as well as to empower end-users by providing them with the infrastructure for expressing and sharing their opinions on the quality of health-related web resources.

  13. Semantic Desktop

    Science.gov (United States)

    Sauermann, Leo; Kiesel, Malte; Schumacher, Kinga; Bernardi, Ansgar

    In diesem Beitrag wird gezeigt, wie der Arbeitsplatz der Zukunft aussehen könnte und wo das Semantic Web neue Möglichkeiten eröffnet. Dazu werden Ansätze aus dem Bereich Semantic Web, Knowledge Representation, Desktop-Anwendungen und Visualisierung vorgestellt, die es uns ermöglichen, die bestehenden Daten eines Benutzers neu zu interpretieren und zu verwenden. Dabei bringt die Kombination von Semantic Web und Desktop Computern besondere Vorteile - ein Paradigma, das unter dem Titel Semantic Desktop bekannt ist. Die beschriebenen Möglichkeiten der Applikationsintegration sind aber nicht auf den Desktop beschränkt, sondern können genauso in Web-Anwendungen Verwendung finden.

  14. Ontology alignment architecture for semantic sensor Web integration.

    Science.gov (United States)

    Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R; Alarcos, Bernardo

    2013-09-18

    Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  15. Ontology Alignment Architecture for Semantic Sensor Web Integration

    Directory of Open Access Journals (Sweden)

    Bernardo Alarcos

    2013-09-01

    Full Text Available Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity. Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity’s names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  16. Audio-Visual and Meaningful Semantic Context Enhancements in Older and Younger Adults.

    Directory of Open Access Journals (Sweden)

    Kirsten E Smayda

    Full Text Available Speech perception is critical to everyday life. Oftentimes noise can degrade a speech signal; however, because of the cues available to the listener, such as visual and semantic cues, noise rarely prevents conversations from continuing. The interaction of visual and semantic cues in aiding speech perception has been studied in young adults, but the extent to which these two cues interact for older adults has not been studied. To investigate the effect of visual and semantic cues on speech perception in older and younger adults, we recruited forty-five young adults (ages 18-35 and thirty-three older adults (ages 60-90 to participate in a speech perception task. Participants were presented with semantically meaningful and anomalous sentences in audio-only and audio-visual conditions. We hypothesized that young adults would outperform older adults across SNRs, modalities, and semantic contexts. In addition, we hypothesized that both young and older adults would receive a greater benefit from a semantically meaningful context in the audio-visual relative to audio-only modality. We predicted that young adults would receive greater visual benefit in semantically meaningful contexts relative to anomalous contexts. However, we predicted that older adults could receive a greater visual benefit in either semantically meaningful or anomalous contexts. Results suggested that in the most supportive context, that is, semantically meaningful sentences presented in the audiovisual modality, older adults performed similarly to young adults. In addition, both groups received the same amount of visual and meaningful benefit. Lastly, across groups, a semantically meaningful context provided more benefit in the audio-visual modality relative to the audio-only modality, and the presence of visual cues provided more benefit in semantically meaningful contexts relative to anomalous contexts. These results suggest that older adults can perceive speech as well as younger

  17. Semantic heterogeneity: comparing new semantic web approaches with those of digital libraries

    OpenAIRE

    Krause, Jürgen

    2008-01-01

    To demonstrate that newer developments in the semantic web community, particularly those based on ontologies (simple knowledge organization system and others) mitigate common arguments from the digital library (DL) community against participation in the Semantic web. The approach is a semantic web discussion focusing on the weak structure of the Web and the lack of consideration given to the semantic content during indexing. The points criticised by the semantic web and ontology approaches ar...

  18. Semantic framework for mapping object-oriented model to semantic web languages.

    Science.gov (United States)

    Ježek, Petr; Mouček, Roman

    2015-01-01

    The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

  19. Semantic annotation in biomedicine: the current landscape.

    Science.gov (United States)

    Jovanović, Jelena; Bagheri, Ebrahim

    2017-09-22

    The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.

  20. Semantic Dysfunction in Women With Schizotypal Personality Disorder

    OpenAIRE

    Niznikiewicz, Margaret A.; Shenton, Martha E.; Voglmaier, Martina; Nestor, Paul G.; Dickey, Chandlee C.; Frumin, Melissa; Seidman, Larry J.; Allen, Christopher G.; McCarley, Robert W.

    2002-01-01

    Objective: This study examined whether early or late processes in semantic networks were abnormal in women with a diagnosis of schizotypal personality disorder. The N400 component of the EEG event-related potentials was used as a probe of semantic processes. Method: Word pairs were presented with short and long stimulus-onset asynchronies to investigate, respectively, early and late semantic processes in 16 women with schizotypal personality disorder and 15 normal female comparison subjects. ...

  1. Programming the semantic web

    CERN Document Server

    Segaran, Toby; Taylor, Jamie

    2009-01-01

    With this book, the promise of the Semantic Web -- in which machines can find, share, and combine data on the Web -- is not just a technical possibility, but a practical reality Programming the Semantic Web demonstrates several ways to implement semantic web applications, using current and emerging standards and technologies. You'll learn how to incorporate existing data sources into semantically aware applications and publish rich semantic data. Each chapter walks you through a single piece of semantic technology and explains how you can use it to solve real problems. Whether you're writing

  2. Recognizable or Not: Towards Image Semantic Quality Assessment for Compression

    Science.gov (United States)

    Liu, Dong; Wang, Dandan; Li, Houqiang

    2017-12-01

    Traditionally, image compression was optimized for the pixel-wise fidelity or the perceptual quality of the compressed images given a bit-rate budget. But recently, compressed images are more and more utilized for automatic semantic analysis tasks such as recognition and retrieval. For these tasks, we argue that the optimization target of compression is no longer perceptual quality, but the utility of the compressed images in the given automatic semantic analysis task. Accordingly, we propose to evaluate the quality of the compressed images neither at pixel level nor at perceptual level, but at semantic level. In this paper, we make preliminary efforts towards image semantic quality assessment (ISQA), focusing on the task of optical character recognition (OCR) from compressed images. We propose a full-reference ISQA measure by comparing the features extracted from text regions of original and compressed images. We then propose to integrate the ISQA measure into an image compression scheme. Experimental results show that our proposed ISQA measure is much better than PSNR and SSIM in evaluating the semantic quality of compressed images; accordingly, adopting our ISQA measure to optimize compression for OCR leads to significant bit-rate saving compared to using PSNR or SSIM. Moreover, we perform subjective test about text recognition from compressed images, and observe that our ISQA measure has high consistency with subjective recognizability. Our work explores new dimensions in image quality assessment, and demonstrates promising direction to achieve higher compression ratio for specific semantic analysis tasks.

  3. Learning the Semantics of Structured Data Sources

    Science.gov (United States)

    Taheriyan, Mohsen

    2015-01-01

    Information sources such as relational databases, spreadsheets, XML, JSON, and Web APIs contain a tremendous amount of structured data, however, they rarely provide a semantic model to describe their contents. Semantic models of data sources capture the intended meaning of data sources by mapping them to the concepts and relationships defined by a…

  4. Semantic data bank

    International Nuclear Information System (INIS)

    Anoreewsky, Evelyne; Nicolas, P.; Grillo, J.P.

    1977-01-01

    A system is proposed for determining semantic relations between lexical items. To do this, a descriptor is associated with each lexical item; two types of algorithms are used to calculate the relationships between descriptors ('similarity' or 'predicativity' relations). This system makes it possible to simulate linguistic experiences. Some results have been predicted and verified experimentally. [fr

  5. Neural Substrates of Semantic Prospection – Evidence from the Dementias

    Science.gov (United States)

    Irish, Muireann; Eyre, Nadine; Dermody, Nadene; O’Callaghan, Claire; Hodges, John R.; Hornberger, Michael; Piguet, Olivier

    2016-01-01

    The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer’s disease (n = 15) and disease-matched behavioral-variant frontotemporal dementia (n = 15), neurodegenerative disorders characterized by significant medial temporal lobe (MTL) and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic) and non-personal (semantic) domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1-weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between gray matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal, and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of

  6. Neural Substrates of Semantic Prospection – Evidence from the Dementias

    Directory of Open Access Journals (Sweden)

    Muireann eIrish

    2016-05-01

    Full Text Available The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer’s disease (n = 15 and disease-matched behavioral-variant frontotemporal dementia (n = 15, neurodegenerative disorders characterized by significant medial temporal lobe and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic and non-personal (semantic domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1 weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between grey matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of

  7. Inquisitive semantics and pragmatics

    NARCIS (Netherlands)

    Groenendijk, J.; Roelofsen, F.; Larrazabal, J.M.; Zubeldia, L.

    2009-01-01

    This paper starts with an informal introduction to inquisitive semantics. After that, we present a formal definition of the semantics, and introduce the basic semantic notions of inquisitiveness and informativeness, in terms of wich we define the semantic categories of questions, assertions, and

  8. Personal semantics: at the crossroads of semantic and episodic memory.

    Science.gov (United States)

    Renoult, Louis; Davidson, Patrick S R; Palombo, Daniela J; Moscovitch, Morris; Levine, Brian

    2012-11-01

    Declarative memory is usually described as consisting of two systems: semantic and episodic memory. Between these two poles, however, may lie a third entity: personal semantics (PS). PS concerns knowledge of one's past. Although typically assumed to be an aspect of semantic memory, it is essentially absent from existing models of knowledge. Furthermore, like episodic memory (EM), PS is idiosyncratically personal (i.e., not culturally-shared). We show that, depending on how it is operationalized, the neural correlates of PS can look more similar to semantic memory, more similar to EM, or dissimilar to both. We consider three different perspectives to better integrate PS into existing models of declarative memory and suggest experimental strategies for disentangling PS from semantic and episodic memory. Copyright © 2012 Elsevier Ltd. All rights reserved.

  9. Phonetic Pause Unites Phonology and Semantics against Morphology and Syntax

    Science.gov (United States)

    Sakarna, Ahmad Khalaf; Mobaideen, Adnan

    2012-01-01

    The present study investigates the phonological effect triggered by the different types of phonetic pause used in Quran on morphology, syntax, and semantics. It argues that Quranic pause provides interesting evidence about the close relation between phonology and semantics, from one side, and semantics, morphology, and syntax, from the other…

  10. Extracting Various Classes of Data From Biological Text Using the Concept of Existence Dependency.

    Science.gov (United States)

    Taha, Kamal

    2015-11-01

    One of the key goals of biological natural language processing (NLP) is the automatic information extraction from biomedical publications. Most current constituency and dependency parsers overlook the semantic relationships between the constituents comprising a sentence and may not be well suited for capturing complex long-distance dependences. We propose in this paper a hybrid constituency-dependency parser for biological NLP information extraction called EDCC. EDCC aims at enhancing the state of the art of biological text mining by applying novel linguistic computational techniques that overcome the limitations of current constituency and dependency parsers outlined earlier, as follows: 1) it determines the semantic relationship between each pair of constituents in a sentence using novel semantic rules; and 2) it applies a semantic relationship extraction model that extracts information from different structural forms of constituents in sentences. EDCC can be used to extract different types of data from biological texts for purposes such as protein function prediction, genetic network construction, and protein-protein interaction detection. We evaluated the quality of EDCC by comparing it experimentally with six systems. Results showed marked improvement.

  11. The Effect of Concurrent Semantic Categorization on Delayed Serial Recall

    Science.gov (United States)

    Acheson, Daniel J.; MacDonald, Maryellen C.; Postle, Bradley R.

    2010-01-01

    The influence of semantic processing on the serial ordering of items in short-term memory was explored using a novel dual-task paradigm. Subjects engaged in two picture judgment tasks while simultaneously performing delayed serial recall. List material varied in the presence of phonological overlap (Experiments 1 and 2) and in semantic content (concrete words in Experiment 1 and 3; nonwords in Experiments 2 and 3). Picture judgments varied in the extent to which they required accessing visual semantic information (i.e., semantic categorization and line orientation judgments). Results showed that, relative to line orientation judgments, engaging in semantic categorization judgments increased the proportion of item ordering errors for concrete lists but did not affect error proportions for nonword lists. Furthermore, although more ordering errors were observed for phonologically similar relative to dissimilar lists, no interactions were observed between the phonological overlap and picture judgment task manipulations. These results thus demonstrate that lexical-semantic representations can affect the serial ordering of items in short-term memory. Furthermore, the dual-task paradigm provides a new method for examining when and how semantic representations affect memory performance. PMID:21058880

  12. SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services.

    Science.gov (United States)

    Gessler, Damian D G; Schiltz, Gary S; May, Greg D; Avraham, Shulamit; Town, Christopher D; Grant, David; Nelson, Rex T

    2009-09-23

    SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at http://sswap.info (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at http://sswap.info/protocol.jsp, developer tools at http://sswap.info/developer.jsp, and a portal to third-party ontologies at http://sswapmeet.sswap.info (a "swap meet"). SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the

  13. Towards the multilingual semantic web principles, methods and applications

    CERN Document Server

    Buitelaar, Paul

    2014-01-01

    To date, the relation between multilingualism and the Semantic Web has not yet received enough attention in the research community. One major challenge for the Semantic Web community is to develop architectures, frameworks and systems that can help in overcoming national and language barriers, facilitating equal access to information produced in different cultures and languages. As such, this volume aims at documenting the state-of-the-art with regard to the vision of a Multilingual Semantic Web, in which semantic information will be accessible in and across multiple languages. The Multiling

  14. Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

    Science.gov (United States)

    Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M.

    2018-05-01

    In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation.

  15. SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media.

    Science.gov (United States)

    Liu, Jing; Zhao, Songzheng; Wang, Gang

    2018-01-01

    With the development of Web 2.0 technology, social media websites have become lucrative but under-explored data sources for extracting adverse drug events (ADEs), which is a serious health problem. Besides ADE, other semantic relation types (e.g., drug indication and beneficial effect) could hold between the drug and adverse event mentions, making ADE relation extraction - distinguishing ADE relationship from other relation types - necessary. However, conducting ADE relation extraction in social media environment is not a trivial task because of the expertise-dependent, time-consuming and costly annotation process, and the feature space's high-dimensionality attributed to intrinsic characteristics of social media data. This study aims to develop a framework for ADE relation extraction using patient-generated content in social media with better performance than that delivered by previous efforts. To achieve the objective, a general semi-supervised ensemble learning framework, SSEL-ADE, was developed. The framework exploited various lexical, semantic, and syntactic features, and integrated ensemble learning and semi-supervised learning. A series of experiments were conducted to verify the effectiveness of the proposed framework. Empirical results demonstrate the effectiveness of each component of SSEL-ADE and reveal that our proposed framework outperforms most of existing ADE relation extraction methods The SSEL-ADE can facilitate enhanced ADE relation extraction performance, thereby providing more reliable support for pharmacovigilance. Moreover, the proposed semi-supervised ensemble methods have the potential of being applied to effectively deal with other social media-based problems. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

    Science.gov (United States)

    Keller, Richard M.; Berrios, Daniel C.; Carvalho, Robert E.; Hall, David R.; Rich, Stephen J.; Sturken, Ian B.; Swanson, Keith J.; Wolfe, Shawn R.

    2004-01-01

    SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including diverse teams of scientists, engineers, and accident investigators. The system provides a customizable, semantically structured information repository that stores work products relevant to multiple projects of differing types. SemanticOrganizer is one of the earliest and largest semantic web applications deployed at NASA to date, and has been used in diverse contexts ranging from the investigation of Space Shuttle Columbia's accident to the search for life on other planets. Although the underlying repository employs a single unified ontology, access control and ontology customization mechanisms make the repository contents appear different for each project team. This paper describes SemanticOrganizer, its customization facilities, and a sampling of its applications. The paper also summarizes some key lessons learned from building and fielding a successful semantic web application across a wide-ranging set of domains with diverse users.

  17. Concealed semantic and episodic autobiographical memory electrified.

    Science.gov (United States)

    Ganis, Giorgio; Schendan, Haline E

    2012-01-01

    Electrophysiology-based concealed information tests (CIT) try to determine whether somebody possesses concealed information about a crime-related item (probe) by comparing event-related potentials (ERPs) between this item and comparison items (irrelevants). Although the broader field is sometimes referred to as "memory detection," little attention has been paid to the precise type of underlying memory involved. This study begins addressing this issue by examining the key distinction between semantic and episodic memory in the autobiographical domain within a CIT paradigm. This study also addresses the issue of whether multiple repetitions of the items over the course of the session habituate the brain responses. Participants were tested in a 3-stimulus CIT with semantic autobiographical probes (their own date of birth) and episodic autobiographical probes (a secret date learned just before the study). Results dissociated these two memory conditions on several ERP components. Semantic probes elicited a smaller frontal N2 than episodic probes, consistent with the idea that the frontal N2 decreases with greater pre-existing knowledge about the item. Likewise, semantic probes elicited a smaller central N400 than episodic probes. Semantic probes also elicited a larger P3b than episodic probes because of their richer meaning. In contrast, episodic probes elicited a larger late positive complex (LPC) than semantic probes, because of the recent episodic memory associated with them. All these ERPs showed a difference between probes and irrelevants in both memory conditions, except for the N400, which showed a difference only in the semantic condition. Finally, although repetition affected the ERPs, it did not reduce the difference between probes and irrelevants. These findings show that the type of memory associated with a probe has both theoretical and practical importance for CIT research.

  18. Concealed semantic and episodic autobiographical memory electrified

    Science.gov (United States)

    Ganis, Giorgio; Schendan, Haline E.

    2013-01-01

    Electrophysiology-based concealed information tests (CIT) try to determine whether somebody possesses concealed information about a crime-related item (probe) by comparing event-related potentials (ERPs) between this item and comparison items (irrelevants). Although the broader field is sometimes referred to as “memory detection,” little attention has been paid to the precise type of underlying memory involved. This study begins addressing this issue by examining the key distinction between semantic and episodic memory in the autobiographical domain within a CIT paradigm. This study also addresses the issue of whether multiple repetitions of the items over the course of the session habituate the brain responses. Participants were tested in a 3-stimulus CIT with semantic autobiographical probes (their own date of birth) and episodic autobiographical probes (a secret date learned just before the study). Results dissociated these two memory conditions on several ERP components. Semantic probes elicited a smaller frontal N2 than episodic probes, consistent with the idea that the frontal N2 decreases with greater pre-existing knowledge about the item. Likewise, semantic probes elicited a smaller central N400 than episodic probes. Semantic probes also elicited a larger P3b than episodic probes because of their richer meaning. In contrast, episodic probes elicited a larger late positive complex (LPC) than semantic probes, because of the recent episodic memory associated with them. All these ERPs showed a difference between probes and irrelevants in both memory conditions, except for the N400, which showed a difference only in the semantic condition. Finally, although repetition affected the ERPs, it did not reduce the difference between probes and irrelevants. These findings show that the type of memory associated with a probe has both theoretical and practical importance for CIT research. PMID:23355816

  19. SCALEUS: Semantic Web Services Integration for Biomedical Applications.

    Science.gov (United States)

    Sernadela, Pedro; González-Castro, Lorena; Oliveira, José Luís

    2017-04-01

    In recent years, we have witnessed an explosion of biological data resulting largely from the demands of life science research. The vast majority of these data are freely available via diverse bioinformatics platforms, including relational databases and conventional keyword search applications. This type of approach has achieved great results in the last few years, but proved to be unfeasible when information needs to be combined or shared among different and scattered sources. During recent years, many of these data distribution challenges have been solved with the adoption of semantic web. Despite the evident benefits of this technology, its adoption introduced new challenges related with the migration process, from existent systems to the semantic level. To facilitate this transition, we have developed Scaleus, a semantic web migration tool that can be deployed on top of traditional systems in order to bring knowledge, inference rules, and query federation to the existent data. Targeted at the biomedical domain, this web-based platform offers, in a single package, straightforward data integration and semantic web services that help developers and researchers in the creation process of new semantically enhanced information systems. SCALEUS is available as open source at http://bioinformatics-ua.github.io/scaleus/ .

  20. Reproducibility and discriminability of brain patterns of semantic categories enhanced by congruent audiovisual stimuli.

    Directory of Open Access Journals (Sweden)

    Yuanqing Li

    Full Text Available One of the central questions in cognitive neuroscience is the precise neural representation, or brain pattern, associated with a semantic category. In this study, we explored the influence of audiovisual stimuli on the brain patterns of concepts or semantic categories through a functional magnetic resonance imaging (fMRI experiment. We used a pattern search method to extract brain patterns corresponding to two semantic categories: "old people" and "young people." These brain patterns were elicited by semantically congruent audiovisual, semantically incongruent audiovisual, unimodal visual, and unimodal auditory stimuli belonging to the two semantic categories. We calculated the reproducibility index, which measures the similarity of the patterns within the same category. We also decoded the semantic categories from these brain patterns. The decoding accuracy reflects the discriminability of the brain patterns between two categories. The results showed that both the reproducibility index of brain patterns and the decoding accuracy were significantly higher for semantically congruent audiovisual stimuli than for unimodal visual and unimodal auditory stimuli, while the semantically incongruent stimuli did not elicit brain patterns with significantly higher reproducibility index or decoding accuracy. Thus, the semantically congruent audiovisual stimuli enhanced the within-class reproducibility of brain patterns and the between-class discriminability of brain patterns, and facilitate neural representations of semantic categories or concepts. Furthermore, we analyzed the brain activity in superior temporal sulcus and middle temporal gyrus (STS/MTG. The strength of the fMRI signal and the reproducibility index were enhanced by the semantically congruent audiovisual stimuli. Our results support the use of the reproducibility index as a potential tool to supplement the fMRI signal amplitude for evaluating multimodal integration.

  1. The semantic structure of gratitude

    Directory of Open Access Journals (Sweden)

    Smirnov, Alexander V.

    2016-06-01

    Full Text Available In the modern social and economic environment of Russia, gratitude might be considered an ambiguous phenomenon. It can have different meaning for a person in different contexts and can manifest itself differently as well (that is, as an expression of sincere feelings or as an element of corruption. In this respect it is topical to investigate the system of meanings and relationships that define the semantic space of gratitude. The goal of the study was the investigation and description of the content and structure of the semantic space of the gratitude phenomenon as well as the determination of male, female, age, and ethnic peculiarities of the expression of gratitude. The objective was achieved by using the semantic differential designed by the authors to investigate attitudes toward gratitude. This investigation was carried out with the participation of 184 respondents (Russians, Tatars, Ukrainians, Jews living in the Russian Federation, Belarus, Kazakhstan, Tajikistan, Israel, Australia, Canada, and the United Kingdom and identifying themselves as representatives of one of these nationalities. The structural components of gratitude were singled out by means of exploratory factor analysis of the empirical data from the designed semantic differential. Gender, age, and ethnic differences were differentiated by means of Student’s t-test. Gratitude can be represented by material and nonmaterial forms as well as by actions in response to help given. The empirical data allowed us to design the ethnically nonspecified semantic structure of gratitude. During the elaboration of the differential, semantic universals of gratitude, which constitute its psychosemantic content, were distinguished. Peculiarities of attitudes toward gratitude by those in different age and gender groups were revealed. Differences in the degree of manifestation of components of the psychosemantic structure of gratitude related to ethnic characteristics were not discovered

  2. The schematic structure of a genre and the logical-semantic relations in an example of argument genre

    Directory of Open Access Journals (Sweden)

    Angela Maria Rossi

    2017-12-01

    Full Text Available From the focus on genre from the School of Sydney (ROSE; MARTIN, 2012 and the Systemic Functional Grammar (HALLIDAY; MATTHIESSEN, 2014, this article aimed to verify how the logic-semantical relation contribute to the organization of the Scheme Structure of a sample of the discussion genre. As predominant, it was verified hypotactical and paratactical relations of intensification, and simplexes.

  3. ERPs, semantic processing and age.

    Science.gov (United States)

    Miyamoto, T; Katayama, J; Koyama, T

    1998-06-01

    ERPs (N400, LPC and CNV) were elicited in two sets of subjects grouped according to age (young vs. elderly) using a word-pair category matching paradigm. Each prime consisted of a Japanese noun (constructed from two to four characters of the Hiragana) followed by one Chinese character (Kanji) as the target, this latter representing one of five semantic categories. There were two equally probable target conditions: match or mismatch. Each target was preceded by a prime, either belonging to, or not belonging to, the same semantic category. The subjects were required to respond with a specified button press to the given target according to the condition. We found RTs to be longer in the elderly subjects and under the mismatch condition. N400 amplitude was reduced in the elderly subjects under the mismatch condition and there was no difference between match and mismatch response, which were similar in amplitude to that under match condition for the young subjects. In addition, the CNV amplitudes were larger in the elderly subjects. These results suggested that functional changes in semantic processing through aging (larger semantic networks and diffuse semantic activation) were the cause of this N400 reduction, attributing a subsidiary role to attentional disturbance. We also discuss the importance of taking age-related changes into consideration in clinical studies.

  4. Word-embeddings Italian semantic spaces: A semantic model for psycholinguistic research

    Directory of Open Access Journals (Sweden)

    Marelli Marco

    2017-01-01

    Full Text Available Distributional semantics has been for long a source of successful models in psycholinguistics, permitting to obtain semantic estimates for a large number of words in an automatic and fast way. However, resources in this respect remain scarce or limitedly accessible for languages different from English. The present paper describes WEISS (Word-Embeddings Italian Semantic Space, a distributional semantic model based on Italian. WEISS includes models of semantic representations that are trained adopting state-of-the-art word-embeddings methods, applying neural networks to induce distributed representations for lexical meanings. The resource is evaluated against two test sets, demonstrating that WEISS obtains a better performance with respect to a baseline encoding word associations. Moreover, an extensive qualitative analysis of the WEISS output provides examples of the model potentialities in capturing several semantic phenomena. Two variants of WEISS are released and made easily accessible via web through the SNAUT graphic interface.

  5. Modeling Views for Semantic Web Using eXtensible Semantic (XSemantic) Nets

    NARCIS (Netherlands)

    Rajugan, R.; Chang, E.; Feng, L.; Dillon, T.; meersman, R; Tari, Z; herrero, p; Méndez, G.; Cavedon, L.; Martin, D.; Hinze, A.; Buchanan, G.

    2005-01-01

    The emergence of Semantic Web (SW) and the related technologies promise to make the web a meaningful experience. Yet, high level modeling, design and querying techniques proves to be a challenging task for organizations that are hoping utilize the SW paradigm for their industrial applications, which

  6. A developer's guide to the semantic web

    CERN Document Server

    Yu, Liyang

    2014-01-01

    The Semantic Web represents a vision for how to make the huge amount of information on the Web automatically processable by machines on a large scale. For this purpose, a whole suite of standards, technologies and related tools have been specified and developed over the last couple of years and they have now become the foundation for numerous new applications. A Developer's Guide to the Semantic Web helps the reader to learn the core standards, key components and underlying concepts. It provides in-depth coverage of both the what-is and how-to aspects of the Semantic Web. From Yu's presentat

  7. A Developer's Guide to the Semantic Web

    CERN Document Server

    Yu, Liyang

    2011-01-01

    The Semantic Web represents a vision for how to make the huge amount of information on the Web automatically processable by machines on a large scale. For this purpose, a whole suite of standards, technologies and related tools have been specified and developed over the last couple of years, and they have now become the foundation for numerous new applications. A Developer's Guide to the Semantic Web helps the reader to learn the core standards, key components, and underlying concepts. It provides in-depth coverage of both the what-is and how-to aspects of the Semantic Web. From Yu's presentat

  8. Semantically Interoperable XML Data.

    Science.gov (United States)

    Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

    2013-09-01

    XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups.

  9. Semantically Interoperable XML Data

    Science.gov (United States)

    Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

    2013-01-01

    XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. PMID:25298789

  10. Semantic Role Labeling

    CERN Document Server

    Palmer, Martha; Xue, Nianwen

    2011-01-01

    This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applyin

  11. Representations for Semantic Learning Webs: Semantic Web Technology in Learning Support

    Science.gov (United States)

    Dzbor, M.; Stutt, A.; Motta, E.; Collins, T.

    2007-01-01

    Recent work on applying semantic technologies to learning has concentrated on providing novel means of accessing and making use of learning objects. However, this is unnecessarily limiting: semantic technologies will make it possible to develop a range of educational Semantic Web services, such as interpretation, structure-visualization, support…

  12. Insights from child development on the relationship between episodic and semantic memory.

    Science.gov (United States)

    Robertson, Erin K; Köhler, Stefan

    2007-11-05

    The present study was motivated by a recent controversy in the neuropsychological literature on semantic dementia as to whether episodic encoding requires semantic processing or whether it can proceed solely based on perceptual processing. We addressed this issue by examining the effect of age-related limitations in semantic competency on episodic memory in 4-6-year-old children (n=67). We administered three different forced-choice recognition memory tests for pictures previously encountered in a single study episode. The tests varied in the degree to which access to semantically encoded information was required at retrieval. Semantic competency predicted recognition performance regardless of whether access to semantic information was required. A direct relation between picture naming at encoding and subsequent recognition was also found for all tests. Our findings emphasize the importance of semantic encoding processes even in retrieval situations that purportedly do not require access to semantic information. They also highlight the importance of testing neuropsychological models of memory in different populations, healthy and brain damaged, at both ends of the developmental continuum.

  13. Varieties of semantic cognition revealed through simultaneous decomposition of intrinsic brain connectivity and behaviour.

    Science.gov (United States)

    Vatansever, Deniz; Bzdok, Danilo; Wang, Hao-Ting; Mollo, Giovanna; Sormaz, Mladen; Murphy, Charlotte; Karapanagiotidis, Theodoros; Smallwood, Jonathan; Jefferies, Elizabeth

    2017-09-01

    Contemporary theories assume that semantic cognition emerges from a neural architecture in which different component processes are combined to produce aspects of conceptual thought and behaviour. In addition to the state-level, momentary variation in brain connectivity, individuals may also differ in their propensity to generate particular configurations of such components, and these trait-level differences may relate to individual differences in semantic cognition. We tested this view by exploring how variation in intrinsic brain functional connectivity between semantic nodes in fMRI was related to performance on a battery of semantic tasks in 154 healthy participants. Through simultaneous decomposition of brain functional connectivity and semantic task performance, we identified distinct components of semantic cognition at rest. In a subsequent validation step, these data-driven components demonstrated explanatory power for neural responses in an fMRI-based semantic localiser task and variation in self-generated thoughts during the resting-state scan. Our findings showed that good performance on harder semantic tasks was associated with relative segregation at rest between frontal brain regions implicated in controlled semantic retrieval and the default mode network. Poor performance on easier tasks was linked to greater coupling between the same frontal regions and the anterior temporal lobe; a pattern associated with deliberate, verbal thematic thoughts at rest. We also identified components that related to qualities of semantic cognition: relatively good performance on pictorial semantic tasks was associated with greater separation of angular gyrus from frontal control sites and greater integration with posterior cingulate and anterior temporal cortex. In contrast, good speech production was linked to the separation of angular gyrus, posterior cingulate and temporal lobe regions. Together these data show that quantitative and qualitative variation in semantic

  14. A METHOD OF EXTRACTING SHORELINE BASED ON SEMANTIC INFORMATION USING DUAL-LENGTH LiDAR DATA

    Directory of Open Access Journals (Sweden)

    C. Yao

    2017-09-01

    Full Text Available Shoreline is a spatial varying separation between water and land. By utilizing dual-wavelength LiDAR point data together with semantic information that shoreline often appears beyond water surface profile and is observable on the beach, the paper generates the shoreline and the details are as follows: (1 Gain the water surface profile: first we obtain water surface by roughly selecting water points based on several features of water body, then apply least square fitting method to get the whole water trend surface. Then we get the ground surface connecting the under -water surface by both TIN progressive filtering method and surface interpolation method. After that, we have two fitting surfaces intersected to get water surface profile of the island. (2 Gain the sandy beach: we grid all points and select the water surface profile grids points as seeds, then extract sandy beach points based on eight-neighborhood method and features, then we get all sandy beaches. (3 Get the island shoreline: first we get the sandy beach shoreline based on intensity information, then we get a threshold value to distinguish wet area and dry area, therefore we get the shoreline of several sandy beaches. In some extent, the shoreline has the same height values within a small area, by using all the sandy shoreline points to fit a plane P, and the intersection line of the ground surface and the shoreline plane P can be regarded as the island shoreline. By comparing with the surveying shoreline, the results show that the proposed method can successfully extract shoreline.

  15. UML 2 Semantics and Applications

    CERN Document Server

    Lano, Kevin

    2009-01-01

    A coherent and integrated account of the leading UML 2 semantics work and the practical applications of UML semantics development With contributions from leading experts in the field, the book begins with an introduction to UML and goes on to offer in-depth and up-to-date coverage of: The role of semantics Considerations and rationale for a UML system model Definition of the UML system model UML descriptive semantics Axiomatic semantics of UML class diagrams The object constraint language Axiomatic semantics of state machines A coalgebraic semantic framework for reasoning about interaction des

  16. Doctor, Teacher, and Stethoscope: Neural Representation of Different Types of Semantic Relations.

    Science.gov (United States)

    Xu, Yangwen; Wang, Xiaosha; Wang, Xiaoying; Men, Weiwei; Gao, Jia-Hong; Bi, Yanchao

    2018-03-28

    Concepts can be related in many ways. They can belong to the same taxonomic category (e.g., "doctor" and "teacher," both in the category of people) or be associated with the same event context (e.g., "doctor" and "stethoscope," both associated with medical scenarios). How are these two major types of semantic relations coded in the brain? We constructed stimuli from three taxonomic categories (people, manmade objects, and locations) and three thematic categories (school, medicine, and sports) and investigated the neural representations of these two dimensions using representational similarity analyses in human participants (10 men and nine women). In specific regions of interest, the left anterior temporal lobe (ATL) and the left temporoparietal junction (TPJ), we found that, whereas both areas had significant effects of taxonomic information, the taxonomic relations had stronger effects in the ATL than in the TPJ ("doctor" and "teacher" closer in ATL neural activity), with the reverse being true for thematic relations ("doctor" and "stethoscope" closer in TPJ neural activity). A whole-brain searchlight analysis revealed that widely distributed regions, mainly in the left hemisphere, represented the taxonomic dimension. Interestingly, the significant effects of the thematic relations were only observed after the taxonomic differences were controlled for in the left TPJ, the right superior lateral occipital cortex, and other frontal, temporal, and parietal regions. In summary, taxonomic grouping is a primary organizational dimension across distributed brain regions, with thematic grouping further embedded within such taxonomic structures. SIGNIFICANCE STATEMENT How are concepts organized in the brain? It is well established that concepts belonging to the same taxonomic categories (e.g., "doctor" and "teacher") share neural representations in specific brain regions. How concepts are associated in other manners (e.g., "doctor" and "stethoscope," which are thematically

  17. Episodic and Semantic Aspects of Memory for Prose.

    Science.gov (United States)

    Dooling, D. James

    This report describes research on Bartlett's theory of constructive memory. In experiment one, schematic retention is related to Tulving's distinction between episodic and semantic memory. With the passage of time, memory for prose reflects decreasing output from episodic memory and increasing output from semantic memory. In experiment two,…

  18. Semantic memory in object use.

    Science.gov (United States)

    Silveri, Maria Caterina; Ciccarelli, Nicoletta

    2009-10-01

    We studied five patients with semantic memory disorders, four with semantic dementia and one with herpes simplex virus encephalitis, to investigate the involvement of semantic conceptual knowledge in object use. Comparisons between patients who had semantic deficits of different severity, as well as the follow-up, showed that the ability to use objects was largely preserved when the deficit was mild but progressively decayed as the deficit became more severe. Naming was generally more impaired than object use. Production tasks (pantomime execution and actual object use) and comprehension tasks (pantomime recognition and action recognition) as well as functional knowledge about objects were impaired when the semantic deficit was severe. Semantic and unrelated errors were produced during object use, but actions were always fluent and patients performed normally on a novel tools task in which the semantic demand was minimal. Patients with severe semantic deficits scored borderline on ideational apraxia tasks. Our data indicate that functional semantic knowledge is crucial for using objects in a conventional way and suggest that non-semantic factors, mainly non-declarative components of memory, might compensate to some extent for semantic disorders and guarantee some residual ability to use very common objects independently of semantic knowledge.

  19. Automaticity Revisited: When Print Doesn't Activate Semantics

    Directory of Open Access Journals (Sweden)

    Elsa Magdalena Labuschagne

    2015-02-01

    Full Text Available It is widely accepted that the presentation of a printed word automatically triggers processing that ends with full semantic activation. This processing, among other characteristics, is held to occur without intention, and cannot be stopped. The results of the present experiment show that this account is problematic in the context of a variant of the Stroop paradigm. Subjects named the print color of words that were either neutral or semantically related to color. When the letters were all colored, all spatially cued, and the spaces between letters were filled with characters from the top of the keyboard (i.e., 4, #, 5, %, 6, and *, color naming yielded a semantically based Stroop effect and a semantically based negative priming effect. In contrast, the same items yielded neither a semantic Stroop effect nor a negative priming effect when a single target letter was uniquely colored and spatially cued. These findings undermine the widespread view that lexical-semantic activation in word reading is automatic in the sense that it occurs without intention and cannot be derailed.

  20. Using a High-Dimensional Graph of Semantic Space to Model Relationships among Words

    Directory of Open Access Journals (Sweden)

    Alice F Jackson

    2014-05-01

    Full Text Available The GOLD model (Graph Of Language Distribution is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA. The superior performance of the GOLD models (big and small suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition.

  1. Using a high-dimensional graph of semantic space to model relationships among words.

    Science.gov (United States)

    Jackson, Alice F; Bolger, Donald J

    2014-01-01

    The GOLD model (Graph Of Language Distribution) is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA). The superior performance of the GOLD models (big and small) suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition (SVD).

  2. Multimodal Semantics Extraction from User-Generated Videos

    Directory of Open Access Journals (Sweden)

    Francesco Cricri

    2012-01-01

    Full Text Available User-generated video content has grown tremendously fast to the point of outpacing professional content creation. In this work we develop methods that analyze contextual information of multiple user-generated videos in order to obtain semantic information about public happenings (e.g., sport and live music events being recorded in these videos. One of the key contributions of this work is a joint utilization of different data modalities, including such captured by auxiliary sensors during the video recording performed by each user. In particular, we analyze GPS data, magnetometer data, accelerometer data, video- and audio-content data. We use these data modalities to infer information about the event being recorded, in terms of layout (e.g., stadium, genre, indoor versus outdoor scene, and the main area of interest of the event. Furthermore we propose a method that automatically identifies the optimal set of cameras to be used in a multicamera video production. Finally, we detect the camera users which fall within the field of view of other cameras recording at the same public happening. We show that the proposed multimodal analysis methods perform well on various recordings obtained in real sport events and live music performances.

  3. Meinongian Semantics and Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    William J. Rapaport

    2013-12-01

    Full Text Available This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks (exemplified by SNePS are discussed; it is argued that only a fully intensional, Meinongian semantics is appropriate for them; and several Meinongian systems are presented.

  4. Geospatial Semantics and the Semantic Web

    CERN Document Server

    Ashish, Naveen

    2011-01-01

    The availability of geographic and geospatial information and services, especially on the open Web has become abundant in the last several years with the proliferation of online maps, geo-coding services, geospatial Web services and geospatially enabled applications. The need for geospatial reasoning has significantly increased in many everyday applications including personal digital assistants, Web search applications, local aware mobile services, specialized systems for emergency response, medical triaging, intelligence analysis and more. Geospatial Semantics and the Semantic Web: Foundation

  5. Neural correlates of concreteness in semantic categorization.

    Science.gov (United States)

    Pexman, Penny M; Hargreaves, Ian S; Edwards, Jodi D; Henry, Luke C; Goodyear, Bradley G

    2007-08-01

    In some contexts, concrete words (CARROT) are recognized and remembered more readily than abstract words (TRUTH). This concreteness effect has historically been explained by two theories of semantic representation: dual-coding [Paivio, A. Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45, 255-287, 1991] and context-availability [Schwanenflugel, P. J. Why are abstract concepts hard to understand? In P. J. Schwanenflugel (Ed.), The psychology of word meanings (pp. 223-250). Hillsdale, NJ: Erlbaum, 1991]. Past efforts to adjudicate between these theories using functional magnetic resonance imaging have produced mixed results. Using event-related functional magnetic resonance imaging, we reexamined this issue with a semantic categorization task that allowed for uniform semantic judgments of concrete and abstract words. The participants were 20 healthy adults. Functional analyses contrasted activation associated with concrete and abstract meanings of ambiguous and unambiguous words. Results showed that for both ambiguous and unambiguous words, abstract meanings were associated with more widespread cortical activation than concrete meanings in numerous regions associated with semantic processing, including temporal, parietal, and frontal cortices. These results are inconsistent with both dual-coding and context-availability theories, as these theories propose that the representations of abstract concepts are relatively impoverished. Our results suggest, instead, that semantic retrieval of abstract concepts involves a network of association areas. We argue that this finding is compatible with a theory of semantic representation such as Barsalou's [Barsalou, L. W. Perceptual symbol systems. Behavioral & Brain Sciences, 22, 577-660, 1999] perceptual symbol systems, whereby concrete and abstract concepts are represented by similar mechanisms but with differences in focal content.

  6. Visual analytics for semantic queries of TerraSAR-X image content

    Science.gov (United States)

    Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

    2015-10-01

    With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain

  7. Semantic dysfunction in women with schizotypal personality disorder.

    Science.gov (United States)

    Niznikiewicz, Margaret A; Shenton, Martha E; Voglmaier, Martina; Nestor, Paul G; Dickey, Chandlee C; Frumin, Melissa; Seidman, Larry J; Allen, Christopher G; McCarley, Robert W

    2002-10-01

    This study examined whether early or late processes in semantic networks were abnormal in women with a diagnosis of schizotypal personality disorder. The N400 component of the EEG event-related potentials was used as a probe of semantic processes. Word pairs were presented with short and long stimulus-onset asynchronies to investigate, respectively, early and late semantic processes in 16 women with schizotypal personality disorder and 15 normal female comparison subjects. Event-related potentials were recorded in response to the last words in a pair. With the short stimulus-onset asynchrony, the N400 amplitude was less negative in the schizotypal personality disorder group than in the normal comparison group. No group differences were found with the long stimulus-onset asynchrony. The finding of a less negative than normal N400 amplitude with the short stimulus-onset asynchrony in women with schizotypal personality disorder supports the hypothesis that persons with this disorder evince an overactivation of semantic networks. The absence of group differences with the long stimulus-onset asynchrony, which is primarily sensitive to processes involved in context integration, suggests that in this group of schizotypal personality disorder subjects, additional demands on working memory may be necessary to bring out the semantic dysfunction.

  8. Phonological and semantic strategies in immediate serial recall.

    Science.gov (United States)

    Campoy, Guillermo; Baddeley, Alan

    2008-05-01

    It has been suggested that certain theoretically important anomalous results in the area of verbal short-term memory could be attributable to differences in strategy. However there are relatively few studies that investigate strategy directly. We describe four experiments, each involving the immediate serial recall of word sequences under baseline control conditions, or preceded by instruction to use a phonological or semantic strategy. Two experiments varied phonological similarity at a presentation rate of one item every 1 or 2 seconds. Both the control and the phonologically instructed group showed clear effects of similarity at both presentation rates, whereas these were largely absent under semantic encoding conditions. Two further experiments manipulated word length at the same two rates. The phonologically instructed groups showed clear effects at both rates, the control group showed a clear effect at the rapid rate which diminished with the slower presentation, while the semantically instructed group showed a relatively weak effect at the rate of one item per second, and a significant reverse effect with slower presentation. The latter finding is interpreted in terms of fortuitous differences in inter-item rated associability between the two otherwise matched word pools, reinforcing our conclusion that the semantically instructed group were indeed encoding semantically. Implications for controlling strategy by instruction are discussed.

  9. Semantic annotation of consumer health questions.

    Science.gov (United States)

    Kilicoglu, Halil; Ben Abacha, Asma; Mrabet, Yassine; Shooshan, Sonya E; Rodriguez, Laritza; Masterton, Kate; Demner-Fushman, Dina

    2018-02-06

    Consumers increasingly use online resources for their health information needs. While current search engines can address these needs to some extent, they generally do not take into account that most health information needs are complex and can only fully be expressed in natural language. Consumer health question answering (QA) systems aim to fill this gap. A major challenge in developing consumer health QA systems is extracting relevant semantic content from the natural language questions (question understanding). To develop effective question understanding tools, question corpora semantically annotated for relevant question elements are needed. In this paper, we present a two-part consumer health question corpus annotated with several semantic categories: named entities, question triggers/types, question frames, and question topic. The first part (CHQA-email) consists of relatively long email requests received by the U.S. National Library of Medicine (NLM) customer service, while the second part (CHQA-web) consists of shorter questions posed to MedlinePlus search engine as queries. Each question has been annotated by two annotators. The annotation methodology is largely the same between the two parts of the corpus; however, we also explain and justify the differences between them. Additionally, we provide information about corpus characteristics, inter-annotator agreement, and our attempts to measure annotation confidence in the absence of adjudication of annotations. The resulting corpus consists of 2614 questions (CHQA-email: 1740, CHQA-web: 874). Problems are the most frequent named entities, while treatment and general information questions are the most common question types. Inter-annotator agreement was generally modest: question types and topics yielded highest agreement, while the agreement for more complex frame annotations was lower. Agreement in CHQA-web was consistently higher than that in CHQA-email. Pairwise inter-annotator agreement proved most

  10. An event-related potential investigation of the relationship between semantic and perceptual levels of representation

    NARCIS (Netherlands)

    Van Schie, H.T.; Wijers, A.A.; Kellenbach, M.L; Stowe, L.A.

    The present study was conducted to investigate relationships between semantic and perceptual levels of representation. A picture - word repetition paradigm was used in which we manipulated the semantic relationship between pictures and words. Experiment I involved two types of trials, one with words

  11. Joint classification and contour extraction of large 3D point clouds

    Science.gov (United States)

    Hackel, Timo; Wegner, Jan D.; Schindler, Konrad

    2017-08-01

    We present an effective and efficient method for point-wise semantic classification and extraction of object contours of large-scale 3D point clouds. What makes point cloud interpretation challenging is the sheer size of several millions of points per scan and the non-grid, sparse, and uneven distribution of points. Standard image processing tools like texture filters, for example, cannot handle such data efficiently, which calls for dedicated point cloud labeling methods. It turns out that one of the major drivers for efficient computation and handling of strong variations in point density, is a careful formulation of per-point neighborhoods at multiple scales. This allows, both, to define an expressive feature set and to extract topologically meaningful object contours. Semantic classification and contour extraction are interlaced problems. Point-wise semantic classification enables extracting a meaningful candidate set of contour points while contours help generating a rich feature representation that benefits point-wise classification. These methods are tailored to have fast run time and small memory footprint for processing large-scale, unstructured, and inhomogeneous point clouds, while still achieving high classification accuracy. We evaluate our methods on the semantic3d.net benchmark for terrestrial laser scans with >109 points.

  12. Discovering EEG resting state alterations of semantic dementia.

    Science.gov (United States)

    Grieder, Matthias; Koenig, Thomas; Kinoshita, Toshihiko; Utsunomiya, Keita; Wahlund, Lars-Olof; Dierks, Thomas; Nishida, Keiichiro

    2016-05-01

    Diagnosis of semantic dementia relies on cost-intensive MRI or PET, although resting EEG markers of other dementias have been reported. Yet the view still holds that resting EEG in patients with semantic dementia is normal. However, studies using increasingly sophisticated EEG analysis methods have demonstrated that slightest alterations of functional brain states can be detected. We analyzed the common four resting EEG microstates (A, B, C, and D) of 8 patients with semantic dementia in comparison with 8 healthy controls and 8 patients with Alzheimer's disease. Topographical differences between the groups were found in microstate classes B and C, while microstate classes A and D were comparable. The data showed that the semantic dementia group had a peculiar microstate E, but the commonly found microstate C was lacking. Furthermore, the presence of microstate E was significantly correlated with lower MMSE and language scores. Alterations in resting EEG can be found in semantic dementia. Topographical shifts in microstate C might be related to semantic memory deficits. This is the first study that discovered resting state EEG abnormality in semantic dementia. The notion that resting EEG in this dementia subtype is normal has to be revised. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  13. The effects of associative and semantic priming in the lexical decision task.

    Science.gov (United States)

    Perea, Manuel; Rosa, Eva

    2002-08-01

    Four lexical decision experiments were conducted to examine under which conditions automatic semantic priming effects can be obtained. Experiments 1 and 2 analyzed associative/semantic effects at several very short stimulus-onset asynchronies (SOAs), whereas Experiments 3 and 4 used a single-presentation paradigm at two response-stimulus intervals (RSIs). Experiment 1 tested associatively related pairs from three semantic categories (synonyms, antonyms, and category coordinates). The results showed reliable associative priming effects at all SOAs. In addition, the correlation between associative strength and magnitude of priming was significant only at the shortest SOA (66 ms). When prime-target pairs were semantically but not associatively related (Experiment 2), reliable priming effects were obtained at SOAs of 83 ms and longer. Using the single-presentation paradigm with a short RSI (200 ms, Experiment 3), the priming effect was equal in size for associative + semantic and for semantic-only pairs (a 21-ms effect). When the RSI was set much longer (1,750 ms, Experiment 4), only the associative + semantic pairs showed a reliable priming effect (23 ms). The results are interpreted in the context of models of semantic memory.

  14. A Complex Network Approach to Distributional Semantic Models.

    Directory of Open Access Journals (Sweden)

    Akira Utsumi

    Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.

  15. Semantic Interpretation of Insar Estimates Using Optical Images with Application to Urban Infrastructure Monitoring

    Science.gov (United States)

    Wang, Y.; Zhu, X. X.

    2015-08-01

    Synthetic aperture radar interferometry (InSAR) has been an established method for long term large area monitoring. Since the launch of meter-resolution spaceborne SAR sensors, the InSAR community has shown that even individual buildings can be monitored in high level of detail. However, the current deformation analysis still remains at a primitive stage of pixel-wise motion parameter inversion and manual identification of the regions of interest. We are aiming at developing an automatic urban infrastructure monitoring approach by combining InSAR and the semantics derived from optical images, so that the deformation analysis can be done systematically in the semantic/object level. This paper explains how we transfer the semantic meaning derived from optical image to the InSAR point clouds, and hence different semantic classes in the InSAR point cloud can be automatically extracted and monitored. Examples on bridges and railway monitoring are demonstrated.

  16. Semantic guidance of eye movements in real-world scenes.

    Science.gov (United States)

    Hwang, Alex D; Wang, Hsueh-Cheng; Pomplun, Marc

    2011-05-25

    The perception of objects in our visual world is influenced by not only their low-level visual features such as shape and color, but also their high-level features such as meaning and semantic relations among them. While it has been shown that low-level features in real-world scenes guide eye movements during scene inspection and search, the influence of semantic similarity among scene objects on eye movements in such situations has not been investigated. Here we study guidance of eye movements by semantic similarity among objects during real-world scene inspection and search. By selecting scenes from the LabelMe object-annotated image database and applying latent semantic analysis (LSA) to the object labels, we generated semantic saliency maps of real-world scenes based on the semantic similarity of scene objects to the currently fixated object or the search target. An ROC analysis of these maps as predictors of subjects' gaze transitions between objects during scene inspection revealed a preference for transitions to objects that were semantically similar to the currently inspected one. Furthermore, during the course of a scene search, subjects' eye movements were progressively guided toward objects that were semantically similar to the search target. These findings demonstrate substantial semantic guidance of eye movements in real-world scenes and show its importance for understanding real-world attentional control. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. From Data to Semantic Information

    Directory of Open Access Journals (Sweden)

    Luciano Floridi

    2003-06-01

    Full Text Available Abstract: There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information.

  18. UltiMatch-NL: a Web service matchmaker based on multiple semantic filters.

    Science.gov (United States)

    Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

    2014-01-01

    In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.

  19. UltiMatch-NL: A Web Service Matchmaker Based on Multiple Semantic Filters

    Science.gov (United States)

    Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

    2014-01-01

    In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters. PMID:25157872

  20. Foundations of semantic web technologies

    CERN Document Server

    Hitzler, Pascal; Rudolph, Sebastian

    2009-01-01

    The Quest for Semantics Building Models Calculating with Knowledge Exchanging Information Semanic Web Technologies RESOURCE DESCRIPTION LANGUAGE (RDF)Simple Ontologies in RDF and RDF SchemaIntroduction to RDF Syntax for RDF Advanced Features Simple Ontologies in RDF Schema Encoding of Special Data Structures An ExampleRDF Formal Semantics Why Semantics? Model-Theoretic Semantics for RDF(S) Syntactic Reasoning with Deduction Rules The Semantic Limits of RDF(S)WEB ONTOLOGY LANGUAGE (OWL) Ontologies in OWL OWL Syntax and Intuitive Semantics OWL Species The Forthcoming OWL 2 StandardOWL Formal Sem

  1. Effect of semantic coherence on episodic memory processes in schizophrenia.

    Science.gov (United States)

    Battal Merlet, Lâle; Morel, Shasha; Blanchet, Alain; Lockman, Hazlin; Kostova, Milena

    2014-12-30

    Schizophrenia is associated with severe episodic retrieval impairment. The aim of this study was to investigate the possibility that schizophrenia patients could improve their familiarity and/or recollection processes by manipulating the semantic coherence of to-be-learned stimuli and using deep encoding. Twelve schizophrenia patients and 12 healthy controls of comparable age, gender, and educational level undertook an associative recognition memory task. The stimuli consisted of pairs of words that were either related or unrelated to a given semantic category. The process dissociation procedure was used to calculate the estimates of familiarity and recollection processes. Both groups showed enhanced memory performances for semantically related words. However, in healthy controls, semantic relatedness led to enhanced recollection, while in schizophrenia patients, it induced enhanced familiarity. The familiarity estimates for related words were comparable in both groups, indicating that familiarity could be used as a compensatory mechanism in schizophrenia patients. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  2. Suggestion-Induced Modulation of Semantic Priming during Functional Magnetic Resonance Imaging

    Science.gov (United States)

    Ulrich, Martin; Kiefer, Markus; Bongartz, Walter; Grön, Georg; Hoenig, Klaus

    2015-01-01

    Using functional magnetic resonance imaging during a primed visual lexical decision task, we investigated the neural and functional mechanisms underlying modulations of semantic word processing through hypnotic suggestions aimed at altering lexical processing of primes. The priming task was to discriminate between target words and pseudowords presented 200 ms after the prime word which was semantically related or unrelated to the target. In a counterbalanced study design, each participant performed the task once at normal wakefulness and once after the administration of hypnotic suggestions to perceive the prime as a meaningless symbol of a foreign language. Neural correlates of priming were defined as significantly lower activations upon semantically related compared to unrelated trials. We found significant suggestive treatment-induced reductions in neural priming, albeit irrespective of the degree of suggestibility. Neural priming was attenuated upon suggestive treatment compared with normal wakefulness in brain regions supporting automatic (fusiform gyrus) and controlled semantic processing (superior and middle temporal gyri, pre- and postcentral gyri, and supplementary motor area). Hence, suggestions reduced semantic word processing by conjointly dampening both automatic and strategic semantic processes. PMID:25923740

  3. Suggestion-Induced Modulation of Semantic Priming during Functional Magnetic Resonance Imaging.

    Directory of Open Access Journals (Sweden)

    Martin Ulrich

    Full Text Available Using functional magnetic resonance imaging during a primed visual lexical decision task, we investigated the neural and functional mechanisms underlying modulations of semantic word processing through hypnotic suggestions aimed at altering lexical processing of primes. The priming task was to discriminate between target words and pseudowords presented 200 ms after the prime word which was semantically related or unrelated to the target. In a counterbalanced study design, each participant performed the task once at normal wakefulness and once after the administration of hypnotic suggestions to perceive the prime as a meaningless symbol of a foreign language. Neural correlates of priming were defined as significantly lower activations upon semantically related compared to unrelated trials. We found significant suggestive treatment-induced reductions in neural priming, albeit irrespective of the degree of suggestibility. Neural priming was attenuated upon suggestive treatment compared with normal wakefulness in brain regions supporting automatic (fusiform gyrus and controlled semantic processing (superior and middle temporal gyri, pre- and postcentral gyri, and supplementary motor area. Hence, suggestions reduced semantic word processing by conjointly dampening both automatic and strategic semantic processes.

  4. IBRI-CASONTO: Ontology-based semantic search engine

    OpenAIRE

    Awny Sayed; Amal Al Muqrishi

    2017-01-01

    The vast availability of information, that added in a very fast pace, in the data repositories creates a challenge in extracting correct and accurate information. Which has increased the competition among developers in order to gain access to technology that seeks to understand the intent researcher and contextual meaning of terms. While the competition for developing an Arabic Semantic Search systems are still in their infancy, and the reason could be traced back to the complexity of Arabic ...

  5. Semantic memory impairment in the earliest phases of Alzheimer's disease

    DEFF Research Database (Denmark)

    Vogel, Asmus; Gade, Anders; Stokholm, Jette

    2005-01-01

    The presence and the nature of semantic memory dysfunction in Alzheimer's disease (AD) have been widely debated. This study aimed to determine the frequency of impaired semantic test performances in mild AD and to study whether incipient semantic impairments could be identified in predementia AD....... Five short neuropsychological tests sensitive to semantic memory and easily applicable in routine practice were administered to 102 patients with mild AD (Mini-Mental State Examination score above 19), 22 predementia AD patients and 58 healthy subjects. 'Category fluency' and 'naming of famous faces......' were the most frequently impaired tests in both patient groups. The study demonstrated that impairments on semantically related tests are common in mild AD and may exist prior to the clinical diagnosis. The results imply that assessment of semantic memory is relevant in the evaluation of patients...

  6. Semantic modeling for theory clarification: The realist vs liberal international relations perspective

    Energy Technology Data Exchange (ETDEWEB)

    Bray, O.H. [Sandia National Labs., Albuquerque, NM (United States)]|[Univ. of New Mexico, Albuquerque, NM (United States). Political Science Dept.

    1994-04-01

    This paper describes a natural language based, semantic information modeling methodology and explores its use and value in clarifying and comparing political science theories and frameworks. As an example, the paper uses this methodology to clarify and compare some of the basic concepts and relationships in the realist (e.g. Waltz) and the liberal (e.g. Rosenau) paradigms for international relations. The methodology can provide three types of benefits: (1) it can clarify and make explicit exactly what is meant by a concept; (2) it can often identify unanticipated implications and consequence of concepts and relationships; and (3) it can help in identifying and operationalizing testable hypotheses.

  7. The role of semantic self-perceptions in temporal distance perceptions toward autobiographical events: the semantic congruence model.

    Science.gov (United States)

    Gebauer, Jochen E; Haddock, Geoffrey; Broemer, Philip; von Hecker, Ulrich

    2013-11-01

    Why do some autobiographical events feel as if they happened yesterday, whereas others feel like ancient history? Such temporal distance perceptions have surprisingly little to do with actual calendar time distance. Instead, psychologists have found that people typically perceive positive autobiographical events as overly recent, while perceiving negative events as overly distant. The origins of this temporal distance bias have been sought in self-enhancement strivings and mood congruence between autobiographical events and chronic mood. As such, past research exclusively focused on the evaluative features of autobiographical events, while neglecting semantic features. To close this gap, we introduce a semantic congruence model. Capitalizing on the Big Two self-perception dimensions, Study 1 showed that high semantic congruence between recalled autobiographical events and trait self-perceptions render the recalled events subjectively recent. Specifically, interpersonally warm (competent) individuals perceived autobiographical events reflecting warmth (competence) as relatively recent, but warm (competent) individuals did not perceive events reflecting competence (warmth) as relatively recent. Study 2 found that conscious perceptions of congruence mediate these effects. Studies 3 and 4 showed that neither mood congruence nor self-enhancement account for these results. Study 5 extended the results from the Big Two to the Big Five self-perception dimensions, while affirming the independence of the semantic congruence model from evaluative influences. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  8. Hybrid ontology for semantic information retrieval model using keyword matching indexing system.

    Science.gov (United States)

    Uthayan, K R; Mala, G S Anandha

    2015-01-01

    Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.

  9. OGC Geographic Information Service Deductive Semantic Reasoning Based on Description Vocabularies Reduction

    Directory of Open Access Journals (Sweden)

    MIAO Lizhi

    2015-09-01

    Full Text Available As geographic information interoperability and sharing developing, more and more interoperable OGC (open geospatial consortium Web services (OWS are generated and published through the internet. These services can facilitate the integration of different scientific applications by searching, finding, and utilizing the large number of scientific data and Web services. However, these services are widely dispersed and hard to be found and utilized with executive semantic retrieval. This is especially true when considering the weak semantic description of geographic information service data. Focusing on semantic retrieval and reasoning of the distributed OWS resources, a deductive and semantic reasoning method is proposed to describe and search relevant OWS resources. Specifically, ①description words are extracted from OWS metadata file to generate GISe ontology-database and instance-database based on geographic ontology according to basic geographic elements category, ②a description words reduction model is put forward to implement knowledge reduction on GISe instance-database based on rough set theory and generate optimized instances database, ③utilizing GISe ontology-database and optimized instance-database to implement semantic inference and reasoning of geographic searching objects is used as an example to demonstrate the efficiency, feasibility and recall ration of the proposed description-word-based reduction model.

  10. Different Loci of Semantic Interference in Picture Naming vs. Word-Picture Matching Tasks

    OpenAIRE

    Harvey, Denise Y.; Schnur, Tatiana T.

    2016-01-01

    Naming pictures and matching words to pictures belonging to the same semantic category impairs performance relative to when stimuli come from different semantic categories (i.e., semantic interference). Despite similar semantic interference phenomena in both picture naming and word-picture matching tasks, the locus of interference has been attributed to different levels of the language system – lexical in naming and semantic in word-picture matching. Although both tasks involve access to shar...

  11. Type-specific proactive interference in patients with semantic and phonological STM deficits.

    Science.gov (United States)

    Harris, Lara; Olson, Andrew; Humphreys, Glyn

    2014-01-01

    Prior neuropsychological evidence suggests that semantic and phonological components of short-term memory (STM) are functionally and neurologically distinct. The current paper examines proactive interference (PI) from semantic and phonological information in two STM-impaired patients, DS (semantic STM deficit) and AK (phonological STM deficit). In Experiment 1 probe recognition tasks with open and closed sets of stimuli were used. Phonological PI was assessed using nonword items, and semantic and phonological PI was assessed using words. In Experiment 2 phonological and semantic PI was elicited by an item recognition probe test with stimuli that bore phonological and semantic relations to the probes. The data suggested heightened phonological PI for the semantic STM patient, and exaggerated effects of semantic PI in the phonological STM case. The findings are consistent with an account of extremely rapid decay of activated type-specific representations in cases of severely impaired phonological and semantic STM.

  12. Masked and unmasked priming effects as a function of semantic relatedness and associative strength.

    Science.gov (United States)

    Sánchez-Casas, Rosa; Ferré, Pilar; Demestre, Josep; García-Chico, Teófilo; García-Albea, José E

    2012-11-01

    The study presented in this paper aimed to investigate the pattern of semantic priming effects, under masked and unmasked conditions, in the lexical decision task, manipulating type of semantic relation and associative strength. Three different kinds of word relations were examined in two experiments: only-semantically related words [e.g., codo (elbow)-rodilla (knee)] and semantic/associative related words with strong [e.g., mesa (table)-silla (chair) and weak association strength [e.g., sapo (toad)-rana (frog)]. In Experiment 1 a masked priming procedure was used with a prime duration of 56 ms, and in Experiment 2, the prime was presented unmasked for 150 ms. The results showed that there were masked priming effects with strong associates, but no evidence of these effects was found with weak associates or only-semantic related word pairs. When the prime was presented unmasked, the three types of relations produced significant priming effects and they were not influenced by association strength.

  13. Automatic processing of semantic relations in fMRI: neural activation during semantic priming of taxonomic and thematic categories.

    Science.gov (United States)

    Sachs, Olga; Weis, Susanne; Zellagui, Nadia; Huber, Walter; Zvyagintsev, Mikhail; Mathiak, Klaus; Kircher, Tilo

    2008-07-07

    Most current models of knowledge organization are based on hierarchical or taxonomic categories (animals, tools). Another important organizational pattern is thematic categorization, i.e. categories held together by external relations, a unifying scene or event (car and garage). The goal of this study was to compare the neural correlates of these categories under automatic processing conditions that minimize strategic influences. We used fMRI to examine neural correlates of semantic priming for category members with a short stimulus onset asynchrony (SOA) of 200 ms as subjects performed a lexical decision task. Four experimental conditions were compared: thematically related words (car-garage); taxonomically related (car-bus); unrelated (car-spoon); non-word trials (car-derf). We found faster reaction times for related than for unrelated prime-target pairs for both thematic and taxonomic categories. However, the size of the thematic priming effect was greater than that of the taxonomic. The imaging data showed signal changes for the taxonomic priming effects in the right precuneus, postcentral gyrus, middle frontal and superior frontal gyri and thematic priming effects in the right middle frontal gyrus and anterior cingulate. The contrast of neural priming effects showed larger signal changes in the right precuneus associated with the taxonomic but not with thematic priming response. We suggest that the greater involvement of precuneus in the processing of taxonomic relations indicates their reduced salience in the knowledge structure compared to more prominent thematic relations.

  14. Retrieval from semantic memory.

    NARCIS (Netherlands)

    Noordman-Vonk, Wietske

    1977-01-01

    The present study has been concerned with the retrieval of semantic information. Retrieving semantic information is a fundamental process in almost any kind of cognitive behavior. The introduction presented the main experimental paradigms and results found in the literature on semantic memory as

  15. Towards Universal Semantic Tagging

    NARCIS (Netherlands)

    Abzianidze, Lasha; Bos, Johan

    2017-01-01

    The paper proposes the task of universal semantic tagging---tagging word tokens with language-neutral, semantically informative tags. We argue that the task, with its independent nature, contributes to better semantic analysis for wide-coverage multilingual text. We present the initial version of

  16. Process-oriented semantic web search

    CERN Document Server

    Tran, DT

    2011-01-01

    The book is composed of two main parts. The first part is a general study of Semantic Web Search. The second part specifically focuses on the use of semantics throughout the search process, compiling a big picture of Process-oriented Semantic Web Search from different pieces of work that target specific aspects of the process.In particular, this book provides a rigorous account of the concepts and technologies proposed for searching resources and semantic data on the Semantic Web. To collate the various approaches and to better understand what the notion of Semantic Web Search entails, this bo

  17. Fine-grained semantic categorization across the abstract and concrete domains.

    Directory of Open Access Journals (Sweden)

    Marta Ghio

    Full Text Available A consolidated approach to the study of the mental representation of word meanings has consisted in contrasting different domains of knowledge, broadly reflecting the abstract-concrete dichotomy. More fine-grained semantic distinctions have emerged in neuropsychological and cognitive neuroscience work, reflecting semantic category specificity, but almost exclusively within the concrete domain. Theoretical advances, particularly within the area of embodied cognition, have more recently put forward the idea that distributed neural representations tied to the kinds of experience maintained with the concepts' referents might distinguish conceptual meanings with a high degree of specificity, including those within the abstract domain. Here we report the results of two psycholinguistic rating studies incorporating such theoretical advances with two main objectives: first, to provide empirical evidence of fine-grained distinctions within both the abstract and the concrete semantic domains with respect to relevant psycholinguistic dimensions; second, to develop a carefully controlled linguistic stimulus set that may be used for auditory as well as visual neuroimaging studies focusing on the parametrization of the semantic space beyond the abstract-concrete dichotomy. Ninety-six participants rated a set of 210 sentences across pre-selected concrete (mouth, hand, or leg action-related and abstract (mental state-, emotion-, mathematics-related categories, with respect either to different semantic domain-related scales (rating study 1, or to concreteness, familiarity, and context availability (rating study 2. Inferential statistics and correspondence analyses highlighted distinguishing semantic and psycholinguistic traits for each of the pre-selected categories, indicating that a simple abstract-concrete dichotomy is not sufficient to account for the entire semantic variability within either domains.

  18. The semantic basis of taste-shape associations

    Directory of Open Access Journals (Sweden)

    Carlos Velasco

    2016-02-01

    Full Text Available Previous research shows that people systematically match tastes with shapes. Here, we assess the extent to which matched taste and shape stimuli share a common semantic space and whether semantically congruent versus incongruent taste/shape associations can influence the speed with which people respond to both shapes and taste words. In Experiment 1, semantic differentiation was used to assess the semantic space of both taste words and shapes. The results suggest a common semantic space containing two principal components (seemingly, intensity and hedonics and two principal clusters, one including round shapes and the taste word “sweet,” and the other including angular shapes and the taste words “salty,” “sour,” and “bitter.” The former cluster appears more positively-valenced whilst less potent than the latter. In Experiment 2, two speeded classification tasks assessed whether congruent versus incongruent mappings of stimuli and responses (e.g., sweet with round versus sweet with angular would influence the speed of participants’ responding, to both shapes and taste words. The results revealed an overall effect of congruence with congruent trials yielding faster responses than their incongruent counterparts. These results are consistent with previous evidence suggesting a close relation (or crossmodal correspondence between tastes and shape curvature that may derive from common semantic coding, perhaps along the intensity and hedonic dimensions.

  19. Concealed semantic and episodic autobiographical memory electrified

    Directory of Open Access Journals (Sweden)

    Giorgio eGanis

    2013-01-01

    Full Text Available Electrophysiology-based concealed information tests (CIT try to determine whether somebody possesses concealed information about a probe item by comparing event-related potentials (ERPs between this item and comparison items (irrelevants. Although the broader field is sometimes referred to as memory detection, little attention has been paid to the precise type of underlying memory involved. This study begins addressing this issue by examining the key distinction between semantic and episodic memory in the autobiographical domain within a CIT paradigm. This study also addressed the issue of whether multiple repetitions of the items over the course of the session habituate the brain responses. Participants were tested in a 3-stimulus CIT with semantic autobiographical probes (their own date of birth and episodic autobiographical probes (a secret date learned just before the study. Results dissociated these two memory conditions on several ERP components. Semantic probes elicited a smaller frontal N2 than episodic probes, consistent with the idea that the frontal N2 decreases with greater pre-existing semantic knowledge about the item. Likewise, semantic probes elicited a smaller central N400 than episodic probes. Semantic probes also elicited a larger P3b than episodic probes because of their richer meaning. In contrast, episodic probes elicited a larger late positive component (LPC than semantic probes, because of the recent episodic memory associated with them. All these ERPs showed a difference between probes and irrelevants in both memory conditions, except for the N400, which showed a difference only in the semantic condition. Finally, although repetition affected the ERPs, it did not reduce the difference between probes and irrelevants. Thus, the type of memory associated with a probe has both theoretical and practical importance for CIT research.

  20. Semantic similarity measure in biomedical domain leverage web search engine.

    Science.gov (United States)

    Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

    2010-01-01

    Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

  1. Lateralized direct and indirect semantic priming effects in subjects with paranormal experiences and beliefs.

    Science.gov (United States)

    Pizzagalli, D; Lehmann, D; Brugger, P

    2001-01-01

    The present investigation tested the hypothesis that, as an aspect of schizotypal thinking, the formation of paranormal beliefs was related to spreading activation characteristics within semantic networks. From a larger student population (n = 117) prescreened for paranormal belief, 12 strong believers and 12 strong disbelievers (all women) were invited for a lateralized semantic priming task with directly and indirectly related prime-target pairs. Believers showed stronger indirect (but not direct) semantic priming effects than disbelievers after left (but not right) visual field stimulation, indicating faster appreciation of distant semantic relations specifically by the right hemisphere, reportedly specialized in coarse rather than focused semantic processing. These results are discussed in the light of recent findings in schizophrenic patients with thought disorders. They suggest that a disinhibition with semantic networks may underlie the formation of paranormal belief. The potential usefulness of work with healthy subjects for neuropsychiatric research is stressed. Copyright 2001 S. Karger AG, Basel

  2. Olfactory memory in the old and very old: relations to episodic and semantic memory and APOE genotype.

    Science.gov (United States)

    Larsson, Maria; Hedner, Margareta; Papenberg, Goran; Seubert, Janina; Bäckman, Lars; Laukka, Erika J

    2016-02-01

    The neuroanatomical organization that underlies olfactory memory is different from that of other memory types. The present work examines olfactory memory in an elderly population-based sample (Swedish National Study on Aging and Care in Kungsholmen) aged 60-100 years (n = 2280). We used structural equation modeling to investigate whether olfactory memory in old age is best conceptualized as a distinct category, differentiated from episodic and semantic memory. Further, potential olfactory dedifferentiation and genetic associations (APOE) to olfactory function in late senescence were investigated. Results are in support of a 3-factor solution where olfactory memory, as indexed by episodic odor recognition and odor identification, is modeled separately from episodic and semantic memory for visual and verbal information. Increasing age was associated with poorer olfactory memory performance, and observed age-related deficits were further exacerbated for carriers of the APOE ε4 allele; these effects tended to be larger for olfactory memory compared to episodic and semantic memory pertaining to other sensory systems (vision, auditory). Finally, stronger correlations between olfactory and episodic memory, indicating dedifferentiation, were observed in the older age groups. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Modulation of alpha oscillations is required for the suppression of semantic interference.

    Science.gov (United States)

    Melnik, Natalia; Mapelli, Igor; Özkurt, Tolga Esat

    2017-10-01

    Recent findings on alpha band oscillations suggest their important role in memory consolidation and suppression of external distractors such as environmental noise. However, less attention was given to the phenomenon of internal distracting information being solely inherent to the stimuli content. Human memory may be prone to internal distractions caused by semantic relatedness between the meaning of words (e.g., atom, neutron, nucleus, etc.) to be encoded, i.e., semantic interference. Our study investigates the brain oscillatory dynamics behind the semantic interference phenomenon, whose possible outcome is known as false memories. In this direction, Deese-Roediger-McDermott word lists were appropriated for a modified Sternberg paradigm in auditory modality. Participants received semantically related and unrelated word lists via headphones while EEG data were acquired. Semantic interference triggered the false memory rates to be higher than those of other types of memory errors. Analysis demonstrated that the upper part of alpha band (∼10-12Hz) power decreases on parieto-occipital channels in the retention interval, prior to the probe item for semantically related condition. Our study elucidates the oscillatory mechanisms behind semantic interference by relying on alpha functional inhibition theory. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. A Defense of Semantic Minimalism

    Science.gov (United States)

    Kim, Su

    2012-01-01

    Semantic Minimalism is a position about the semantic content of declarative sentences, i.e., the content that is determined entirely by syntax. It is defined by the following two points: "Point 1": The semantic content is a complete/truth-conditional proposition. "Point 2": The semantic content is useful to a theory of…

  5. Productive Extension of Semantic Memory in School-Aged Children: Relations with Reading Comprehension and Deployment of Cognitive Resources

    Science.gov (United States)

    Bauer, Patricia J.; Blue, Shala N.; Xu, Aoxiang; Esposito, Alena G.

    2016-01-01

    We investigated 7- to 10-year-old children's productive extension of semantic memory through self-generation of new factual knowledge derived through integration of separate yet related facts learned through instruction or through reading. In Experiment 1, an experimenter read the to-be-integrated facts. Children successfully learned and…

  6. The effects of bilingual language proficiency on recall accuracy and semantic clustering in free recall output: evidence for shared semantic associations across languages.

    Science.gov (United States)

    Francis, Wendy S; Taylor, Randolph S; Gutiérrez, Marisela; Liaño, Mary K; Manzanera, Diana G; Penalver, Renee M

    2018-05-19

    Two experiments investigated how well bilinguals utilise long-standing semantic associations to encode and retrieve semantic clusters in verbal episodic memory. In Experiment 1, Spanish-English bilinguals (N = 128) studied and recalled word and picture sets. Word recall was equivalent in L1 and L2, picture recall was better in L1 than in L2, and the picture superiority effect was stronger in L1 than in L2. Semantic clustering in word and picture recall was equivalent in L1 and L2. In Experiment 2, Spanish-English bilinguals (N = 128) and English-speaking monolinguals (N = 128) studied and recalled word sequences that contained semantically related pairs. Data were analyzed using a multinomial processing tree approach, the pair-clustering model. Cluster formation was more likely for semantically organised than for randomly ordered word sequences. Probabilities of cluster formation, cluster retrieval, and retrieval of unclustered items did not differ across languages or language groups. Language proficiency has little if any impact on the utilisation of long-standing semantic associations, which are language-general.

  7. TOWARD SEMANTIC WEB INFRASTRUCTURE FOR SPATIAL FEATURES' INFORMATION

    Directory of Open Access Journals (Sweden)

    R. Arabsheibani

    2015-12-01

    Full Text Available The Web and its capabilities can be employed as a tool for data and information integration if comprehensive datasets and appropriate technologies and standards enable the web with interpretation and easy alignment of data and information. Semantic Web along with the spatial functionalities enable the web to deal with the huge amount of data and information. The present study investigate the advantages and limitations of the Spatial Semantic Web and compare its capabilities with relational models in order to build a spatial data infrastructure. An architecture is proposed and a set of criteria is defined for the efficiency evaluation. The result demonstrate that when using the data with special characteristics such as schema dynamicity, sparse data or available relations between the features, the spatial semantic web and graph databases with spatial operations are preferable.

  8. Musical and verbal semantic memory: two distinct neural networks?

    Science.gov (United States)

    Groussard, M; Viader, F; Hubert, V; Landeau, B; Abbas, A; Desgranges, B; Eustache, F; Platel, H

    2010-02-01

    Semantic memory has been investigated in numerous neuroimaging and clinical studies, most of which have used verbal or visual, but only very seldom, musical material. Clinical studies have suggested that there is a relative neural independence between verbal and musical semantic memory. In the present study, "musical semantic memory" is defined as memory for "well-known" melodies without any knowledge of the spatial or temporal circumstances of learning, while "verbal semantic memory" corresponds to general knowledge about concepts, again without any knowledge of the spatial or temporal circumstances of learning. Our aim was to compare the neural substrates of musical and verbal semantic memory by administering the same type of task in each modality. We used high-resolution PET H(2)O(15) to observe 11 young subjects performing two main tasks: (1) a musical semantic memory task, where the subjects heard the first part of familiar melodies and had to decide whether the second part they heard matched the first, and (2) a verbal semantic memory task with the same design, but where the material consisted of well-known expressions or proverbs. The musical semantic memory condition activated the superior temporal area and inferior and middle frontal areas in the left hemisphere and the inferior frontal area in the right hemisphere. The verbal semantic memory condition activated the middle temporal region in the left hemisphere and the cerebellum in the right hemisphere. We found that the verbal and musical semantic processes activated a common network extending throughout the left temporal neocortex. In addition, there was a material-dependent topographical preference within this network, with predominantly anterior activation during musical tasks and predominantly posterior activation during semantic verbal tasks. Copyright (c) 2009 Elsevier Inc. All rights reserved.

  9. Scientific Datasets: Discovery and Aggregation for Semantic Interpretation.

    Science.gov (United States)

    Lopez, L. A.; Scott, S.; Khalsa, S. J. S.; Duerr, R.

    2015-12-01

    One of the biggest challenges that interdisciplinary researchers face is finding suitable datasets in order to advance their science; this problem remains consistent across multiple disciplines. A surprising number of scientists, when asked what tool they use for data discovery, reply "Google", which is an acceptable solution in some cases but not even Google can find -or cares to compile- all the data that's relevant for science and particularly geo sciences. If a dataset is not discoverable through a well known search provider it will remain dark data to the scientific world.For the past year, BCube, an EarthCube Building Block project, has been developing, testing and deploying a technology stack capable of data discovery at web-scale using the ultimate dataset: The Internet. This stack has 2 principal components, a web-scale crawling infrastructure and a semantic aggregator. The web-crawler is a modified version of Apache Nutch (the originator of Hadoop and other big data technologies) that has been improved and tailored for data and data service discovery. The second component is semantic aggregation, carried out by a python-based workflow that extracts valuable metadata and stores it in the form of triples through the use semantic technologies.While implementing the BCube stack we have run into several challenges such as a) scaling the project to cover big portions of the Internet at a reasonable cost, b) making sense of very diverse and non-homogeneous data, and lastly, c) extracting facts about these datasets using semantic technologies in order to make them usable for the geosciences community. Despite all these challenges we have proven that we can discover and characterize data that otherwise would have remained in the dark corners of the Internet. Having all this data indexed and 'triplelized' will enable scientists to access a trove of information relevant to their work in a more natural way. An important characteristic of the BCube stack is that all

  10. A Geospatial Semantic Enrichment and Query Service for Geotagged Photographs

    Science.gov (United States)

    Ennis, Andrew; Nugent, Chris; Morrow, Philip; Chen, Liming; Ioannidis, George; Stan, Alexandru; Rachev, Preslav

    2015-01-01

    With the increasing abundance of technologies and smart devices, equipped with a multitude of sensors for sensing the environment around them, information creation and consumption has now become effortless. This, in particular, is the case for photographs with vast amounts being created and shared every day. For example, at the time of this writing, Instagram users upload 70 million photographs a day. Nevertheless, it still remains a challenge to discover the “right” information for the appropriate purpose. This paper describes an approach to create semantic geospatial metadata for photographs, which can facilitate photograph search and discovery. To achieve this we have developed and implemented a semantic geospatial data model by which a photograph can be enrich with geospatial metadata extracted from several geospatial data sources based on the raw low-level geo-metadata from a smartphone photograph. We present the details of our method and implementation for searching and querying the semantic geospatial metadata repository to enable a user or third party system to find the information they are looking for. PMID:26205265

  11. Learning Semantic Tags from Big Data for Clinical Text Representation.

    Science.gov (United States)

    Li, Yanpeng; Liu, Hongfang

    2015-01-01

    In clinical text mining, it is one of the biggest challenges to represent medical terminologies and n-gram terms in sparse medical reports using either supervised or unsupervised methods. Addressing this issue, we propose a novel method for word and n-gram representation at semantic level. We first represent each word by its distance with a set of reference features calculated by reference distance estimator (RDE) learned from labeled and unlabeled data, and then generate new features using simple techniques of discretization, random sampling and merging. The new features are a set of binary rules that can be interpreted as semantic tags derived from word and n-grams. We show that the new features significantly outperform classical bag-of-words and n-grams in the task of heart disease risk factor extraction in i2b2 2014 challenge. It is promising to see that semantics tags can be used to replace the original text entirely with even better prediction performance as well as derive new rules beyond lexical level.

  12. IBRI-CASONTO: Ontology-based semantic search engine

    Directory of Open Access Journals (Sweden)

    Awny Sayed

    2017-11-01

    Full Text Available The vast availability of information, that added in a very fast pace, in the data repositories creates a challenge in extracting correct and accurate information. Which has increased the competition among developers in order to gain access to technology that seeks to understand the intent researcher and contextual meaning of terms. While the competition for developing an Arabic Semantic Search systems are still in their infancy, and the reason could be traced back to the complexity of Arabic Language. It has a complex morphological, grammatical and semantic aspects, as it is a highly inflectional and derivational language. In this paper, we try to highlight and present an Ontological Search Engine called IBRI-CASONTO for Colleges of Applied Sciences, Oman. Our proposed engine supports both Arabic and English language. It is also employed two types of search which are a keyword-based search and a semantics-based search. IBRI-CASONTO is based on different technologies such as Resource Description Framework (RDF data and Ontological graph. The experiments represent in two sections, first it shows a comparison among Entity-Search and the Classical-Search inside the IBRI-CASONTO itself, second it compares the Entity-Search of IBRI-CASONTO with currently used search engines, such as Kngine, Wolfram Alpha and the most popular engine nowadays Google, in order to measure their performance and efficiency.

  13. Open semantic analysis: The case of word level semantics in Danish

    DEFF Research Database (Denmark)

    Nielsen, Finn Årup; Hansen, Lars Kai

    2017-01-01

    The present research is motivated by the need for accessible and efficient tools for automated semantic analysis in Danish. We are interested in tools that are completely open, so they can be used by a critical public, in public administration, non-governmental organizations and businesses. We...... describe data-driven models for Danish semantic relatedness, word intrusion and sentiment prediction. Open Danish corpora were assembled and unsupervised learning implemented for explicit semantic analysis and with Gensim’s Word2vec model. We evaluate the performance of the two models on three different...... annotated word datasets. We test the semantic representations’ alignment with single word sentiment using supervised learning. We find that logistic regression and large random forests perform well with Word2vec features....

  14. Processing of visual semantic information to concrete words : temporal dynamics and neural mechanisms indicated by event-related brain potentials

    NARCIS (Netherlands)

    van Schie, Hein T.; Wijers, Albertus A.; Mars, Rogier B.; Benjamins, Jeroen S.; Stowe, Laurie A.

    2005-01-01

    Event-related brain potentials were used to study the retrieval of visual semantic information to concrete words, and to investigate possible structural overlap between visual object working memory and concreteness effects in word processing. Subjects performed an object working memory task that

  15. Processing of visual semantic information to concrete words: temporal dynamics and neural mechanisms indicated by event-related brain potentials

    NARCIS (Netherlands)

    Schie, H.T. van; Wijers, A.A.; Mars, R.B.; Benjamins, J.S.; Stowe, L.A.

    2005-01-01

    Event-related brain potentials were used to study the retrieval of visual semantic information to concrete words, and to investigate possible structural overlap between visual object working memory and concreteness effects in word processing. Subjects performed an object working memory task that

  16. Semantic Technologies for Nuclear Knowledge Modelling and Applications

    International Nuclear Information System (INIS)

    Beraha, D.; Gladyshev, M.

    2016-01-01

    Full text: The IAEA has been engaged in working with Member States to preserve and enhance nuclear knowledge, and in supporting wide dissemination of safety related technical and technological information enhancing nuclear safety. The knowledge organization systems (ontologies, taxonomies, thesauri, etc.) provide one of the means to model and structure a given knowledge domain. The significance of knowledge organization systems (KOS) has been greatly enhanced by the evolution of the semantic technologies, enabling machines to “understand” the concepts described in a KOS, and to use them in a variety of applications. Over recent years semantic technologies have emerged as efficient means to improve access to information and knowledge. The Semantic Web Standards play an important role in creating an infrastructure of interoperable data sources based on principles of Linked Data. The status of utilizing semantic technologies in the nuclear domain is shortly reviewed, noting that such technologies are in their early stage of adoption, and considering some aspects which are specific to nuclear knowledge management. Several areas are described where semantic technologies are already deployed, and other areas are indicated where applications based on semantic technologies will have a strong impact on nuclear knowledge management in the near future. (author

  17. Concept indexing and expansion for social multimedia websites based on semantic processing and graph analysis

    Science.gov (United States)

    Lin, Po-Chuan; Chen, Bo-Wei; Chang, Hangbae

    2016-07-01

    This study presents a human-centric technique for social video expansion based on semantic processing and graph analysis. The objective is to increase metadata of an online video and to explore related information, thereby facilitating user browsing activities. To analyze the semantic meaning of a video, shots and scenes are firstly extracted from the video on the server side. Subsequently, this study uses annotations along with ConceptNet to establish the underlying framework. Detailed metadata, including visual objects and audio events among the predefined categories, are indexed by using the proposed method. Furthermore, relevant online media associated with each category are also analyzed to enrich the existing content. With the above-mentioned information, users can easily browse and search the content according to the link analysis and its complementary knowledge. Experiments on a video dataset are conducted for evaluation. The results show that our system can achieve satisfactory performance, thereby demonstrating the feasibility of the proposed idea.

  18. Semantic activation by Japanese kanji: evidence from event-related potentials.

    Science.gov (United States)

    Hayashi, M; Kayamoto, Y; Tanaka, H; Yamada, J

    1998-04-01

    In a character-judgment paradigm, the subject quickly pressed a key when a hiragana (Japanese syllabary) appeared on a display and did nothing when a kanji (Japanese logograph) appeared. The amplitude of the N400 component was compared when four types of visual stimuli were used: (Type 1) single kanji--Grade 1- to 3-level words, (Type 2) single kanji--Grade 1- to 3-level bound morphemes, (Type 3) single kanji--high school- and college-level bound morphemes, and (Type 4) obsolete kanji. Analysis showed that N400 was largest in the temporal-occipital areas for the Type 1 stimuli and larger in the right parietal area for Type 2 than Type 3 stimuli. The analyses of N400 to semantic stimulations have been conducted and discussed in terms of their meaningfulness, age when writing of these kanji was mastered, and linguistic status (kanji versus nonkanji). Most interestingly, the Types 3 and 4 kanji did not activate semantic responses, showing that they did not function as linguistic units, i.e., kanji, in the mental lexicon.

  19. Data Cleaning and Semantic Improvement in Biological Databases

    Directory of Open Access Journals (Sweden)

    Apiletti Daniele

    2006-12-01

    Full Text Available Public genomic and proteomic databases can be affected by a variety of errors. These errors may involve either the description or the meaning of data (namely, syntactic or semantic errors. We focus our analysis on the detection of semantic errors, in order to verify the accuracy of the stored information. In particular, we address the issue of data constraints and functional dependencies among attributes in a given relational database. Constraints and dependencies show semantics among attributes in a database schema and their knowledge may be exploited to improve data quality and integration in database design, and to perform query optimization and dimensional reduction.

  20. Semantic processing in deaf and hard-of-hearing children: Large N400 mismatch effects in brain responses, despite poor semantic ability

    Directory of Open Access Journals (Sweden)

    Petter Kallioinen

    2016-08-01

    Full Text Available Difficulties in auditory and phonological processing affect semantic processing in speech comprehension of deaf and hard-of-hearing (DHH children. However, little is known about brain responses of semantic processing in this group. We investigated event-related potentials (ERPs in DHH children with cochlear implants (CI and/or hearing aids (HA, and in normally hearing controls (NH. We used a semantic priming task with spoken word primes followed by picture targets. In both DHH children and controls, response differences between matching and mismatching targets revealed a typical N400-effect associated with semantic processing. Children with CI had the largest mismatch response despite poor semantic abilities overall, children with CI also had the largest ERP differentiation between mismatch types, with small effects of within-category mismatches (target from same category as prime and large effects between-category mismatches (were target is from a different category than prime. NH and HA children had similar responses to both mismatch types. While the large and differentiated ERP responses in the CI group were unexpected and should be interpreted with caution, the results could reflect less precision in semantic processing among children with CI, or a stronger reliance on predictive processing.

  1. Semantic Neighborhood Effects for Abstract versus Concrete Words.

    Science.gov (United States)

    Danguecan, Ashley N; Buchanan, Lori

    2016-01-01

    Studies show that semantic effects may be task-specific, and thus, that semantic representations are flexible and dynamic. Such findings are critical to the development of a comprehensive theory of semantic processing in visual word recognition, which should arguably account for how semantic effects may vary by task. It has been suggested that semantic effects are more directly examined using tasks that explicitly require meaning processing relative to those for which meaning processing is not necessary (e.g., lexical decision task). The purpose of the present study was to chart the processing of concrete versus abstract words in the context of a global co-occurrence variable, semantic neighborhood density (SND), by comparing word recognition response times (RTs) across four tasks varying in explicit semantic demands: standard lexical decision task (with non-pronounceable non-words), go/no-go lexical decision task (with pronounceable non-words), progressive demasking task, and sentence relatedness task. The same experimental stimulus set was used across experiments and consisted of 44 concrete and 44 abstract words, with half of these being low SND, and half being high SND. In this way, concreteness and SND were manipulated in a factorial design using a number of visual word recognition tasks. A consistent RT pattern emerged across tasks, in which SND effects were found for abstract (but not necessarily concrete) words. Ultimately, these findings highlight the importance of studying interactive effects in word recognition, and suggest that linguistic associative information is particularly important for abstract words.

  2. Processing Relative Clause Extractions in Swedish

    Directory of Open Access Journals (Sweden)

    Damon Tutunjian

    2017-12-01

    Full Text Available Relative clauses are considered strong islands for extraction across languages. Swedish comprises a well-known exception, allegedly allowing extraction from relative clauses (RCE, raising the possibility that island constraints may be subject to “deep variation” between languages. One alternative is that such exceptions are only illusory and represent “surface variation” attributable to independently motivated syntactic properties. Yet, to date, no surface account has proven tenable for Swedish RCEs. The present study uses eyetracking while reading to test whether the apparent acceptability of Swedish RCEs has any processing correlates at the point of filler integration compared to uncontroversial strong island violations. Experiment 1 tests RCE against licit that-clause extraction (TCE, illicit extraction from a non-restrictive relative clause (NRCE, and an intransitive control. For this, RCE was found to pattern similarly to TCE at the point of integration in early measures, but between TCE and NRCE in total durations. Experiment 2 uses RCE and extraction from a subject NP island (SRCE to test the hypothesis that only non-islands will show effects of implausible filler-verb dependencies. RCE showed sensitivity to the plausibility manipulation across measures at the first potential point of filler integration, whereas such effects were limited to late measures for SRCE. In addition, structural facilitation was seen across measures for RCE relative to SRCE. We propose that our results are compatible with RCEs being licit weak island extractions in Swedish, and that the overall picture speaks in favor of a surface rather than a deep variation approach to the lack of island effects in Swedish RCEs.

  3. Pascal Semantics by a Combination of Denotational Semantics and High-level Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt; Schmidt, Erik Meineche

    1986-01-01

    This paper describes the formal semantics of a subset of PASCAL, by means of a semantic model based on a combination of denotational semantics and high-level Petri nets. It is our intention that the paper can be used as part of the written material for an introductory course in computer science....

  4. [Electrophysiological bases of semantic processing of objects].

    Science.gov (United States)

    Kahlaoui, Karima; Baccino, Thierry; Joanette, Yves; Magnié, Marie-Noële

    2007-02-01

    How pictures and words are stored and processed in the human brain constitute a long-standing question in cognitive psychology. Behavioral studies have yielded a large amount of data addressing this issue. Generally speaking, these data show that there are some interactions between the semantic processing of pictures and words. However, behavioral methods can provide only limited insight into certain findings. Fortunately, Event-Related Potential (ERP) provides on-line cues about the temporal nature of cognitive processes and contributes to the exploration of their neural substrates. ERPs have been used in order to better understand semantic processing of words and pictures. The main objective of this article is to offer an overview of the electrophysiologic bases of semantic processing of words and pictures. Studies presented in this article showed that the processing of words is associated with an N 400 component, whereas pictures elicited both N 300 and N 400 components. Topographical analysis of the N 400 distribution over the scalp is compatible with the idea that both image-mediated concrete words and pictures access an amodal semantic system. However, given the distinctive N 300 patterns, observed only during picture processing, it appears that picture and word processing rely upon distinct neuronal networks, even if they end up activating more or less similar semantic representations.

  5. Toponym Extraction and Disambiguation Enhancement Using Loops of Feedback

    NARCIS (Netherlands)

    Habib, Mena Badieh; van Keulen, Maurice; Fred, A.; Dietz, J.L.G.; Liu, K.; Filipe, J.

    2013-01-01

    Toponym extraction and disambiguation have received much attention in recent years. Typical fields addressing these topics are information retrieval, natural language processing, and semantic web. This paper addresses two problems with toponym extraction and disambiguation. First, almost no existing

  6. Interdiscursive Character of Semantic Development of Coreferential Metaphors

    Directory of Open Access Journals (Sweden)

    Мансур Фарвазович Гайнаншин

    2016-12-01

    Full Text Available The article is devoted to establishing the character of semantic development involving coreferential metaphors in interdiscursive space. The solution of this problem is aimed at determining semantic relations between different links in chains made up by a number of coreferential metaphors that share the property of variant imagery nomination. The task is implemented within the boundaries of an interdiscourse viewed as a minimum cultural associative context. Empirical data have been drawn from financial and economic texts in electronic and online versions of leading English mass media resources. The meanings of key language units that underlie metaphoric designations of economic notions are clarified with the help of general English language dictionaries and culturological reference books. The analysis of selected examples is carried out based on componential, contextual, discursive, pragmatic analyses and procedures of semantic interpretation supplemented by linguaculturological methods. The investigation allows us to draw the following conclusions: semantic development of coreferential metaphors occurs on two levels: between variant imagery nominations within metaphorical chains M1 + M2 + M3 + ... Мn and between the head metaphor and submetaphors M1 ® ma + mb + mc +... mn; it has proved the role of interdiscursive contextual relations between metaphors having the same type of reference; it has shown the participation of imagery nominations within coreferential chains in the process of sense profiling; it has demonstrated intensification of semantic tension resulting from metaphoric density in coreferential blocks signaling greater synergetic effect produced on the reader.

  7. Semantic Web technologies for the big data in life sciences.

    Science.gov (United States)

    Wu, Hongyan; Yamaguchi, Atsuko

    2014-08-01

    The life sciences field is entering an era of big data with the breakthroughs of science and technology. More and more big data-related projects and activities are being performed in the world. Life sciences data generated by new technologies are continuing to grow in not only size but also variety and complexity, with great speed. To ensure that big data has a major influence in the life sciences, comprehensive data analysis across multiple data sources and even across disciplines is indispensable. The increasing volume of data and the heterogeneous, complex varieties of data are two principal issues mainly discussed in life science informatics. The ever-evolving next-generation Web, characterized as the Semantic Web, is an extension of the current Web, aiming to provide information for not only humans but also computers to semantically process large-scale data. The paper presents a survey of big data in life sciences, big data related projects and Semantic Web technologies. The paper introduces the main Semantic Web technologies and their current situation, and provides a detailed analysis of how Semantic Web technologies address the heterogeneous variety of life sciences big data. The paper helps to understand the role of Semantic Web technologies in the big data era and how they provide a promising solution for the big data in life sciences.

  8. Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

    Science.gov (United States)

    He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

    2017-11-01

    The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments.

  9. Processing Relative Clause Extractions in Swedish

    OpenAIRE

    Tutunjian, Damon; Heinat, Fredrik; Klingvall, Eva; Wiklund, Anna-Lena

    2017-01-01

    Relative clauses are considered strong islands for extraction across languages. Swedish comprises a well-known exception, allegedly allowing extraction from relative clauses (RCE), raising the possibility that island constraints may be subject to “deep variation” between languages. One alternative is that such exceptions are only illusory and represent “surface variation” attributable to independently motivated syntactic properties. Yet, to date, no surface account has proven tenable for Swed...

  10. Dynamic information processing states revealed through neurocognitive models of object semantics

    Science.gov (United States)

    Clarke, Alex

    2015-01-01

    Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

  11. A semantic web ontology for small molecules and their biological targets.

    Science.gov (United States)

    Choi, Jooyoung; Davis, Melissa J; Newman, Andrew F; Ragan, Mark A

    2010-05-24

    A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

  12. 2nd International Conference on Proof-Theoretic Semantics

    CERN Document Server

    Schroeder-Heister, Peter

    2016-01-01

    This volume is the first ever collection devoted to the field of proof-theoretic semantics. Contributions address topics including the systematics of introduction and elimination rules and proofs of normalization, the categorial characterization of deductions, the relation between Heyting's and Gentzen's approaches to meaning, knowability paradoxes, proof-theoretic foundations of set theory, Dummett's justification of logical laws, Kreisel's theory of constructions, paradoxical reasoning, and the defence of model theory. The field of proof-theoretic semantics has existed for almost 50 years, but the term itself was proposed by Schroeder-Heister in the 1980s. Proof-theoretic semantics explains the meaning of linguistic expressions in general and of logical constants in particular in terms of the notion of proof. This volume emerges from presentations at the Second International Conference on Proof-Theoretic Semantics in Tübingen in 2013, where contributing authors were asked to provide a self-contained descri...

  13. Attenuation of deep semantic processing during mind wandering: an event-related potential study.

    Science.gov (United States)

    Xu, Judy; Friedman, David; Metcalfe, Janet

    2018-03-21

    Although much research shows that early sensory and attentional processing is affected by mind wandering, the effect of mind wandering on deep (i.e. semantic) processing is relatively unexplored. To investigate this relation, we recorded event-related potentials as participants studied English-Spanish word pairs, one at a time, while being intermittently probed for whether they were 'on task' or 'mind wandering'. Both perceptual processing, indexed by the P2 component, and deep processing, indexed by a late, sustained slow wave maximal at parietal electrodes, was attenuated during periods preceding participants' mind wandering reports. The pattern when participants were on task, rather than mind wandering, is similar to the subsequent memory or difference in memory effect. These results support previous findings of sensory attenuation during mind wandering, and extend them to a long-duration slow wave by suggesting that the deeper and more sustained levels of processing are also disrupted.

  14. Does semantic impairment explain surface dyslexia? VLSM evidence for a double dissociation between regularization errors in reading and semantic errors in picture naming

    Directory of Open Access Journals (Sweden)

    Sara Pillay

    2014-04-01

    adjacent posterior inferior temporal gyrus (blue in figure 1. In contrast, semantic errors during picture naming (red and pink in figure 1 and impaired performance on the semantic matching task (yellow and pink in figure 1 were correlated with more anterior temporal lobe damage and with inferior frontal gyrus involvement. There was substantial overlap between lesion correlates for the two explicit semantic tasks (pink in figure 1, but none between these areas and those correlated with regularization errors. This double dissociation is difficult to accommodate in terms of a common impairment underlying semantic deficits and regularization errors. Lesions in relatively anterior temporal regions appear to produce semantic deficits but not regularization errors, whereas more posterior temporal lesions produce regularization errors but not explicit semantic errors. One possibility is that this posterior temporal region stores whole word representations that do not include semantic information. Alternatively, these representations may include highly abstract and word-specific semantic information useful for computing phonology but not for more complex semantic tasks.

  15. Semantic organization in children with Cochlear Implants: Computational analysis of verbal fluency

    Directory of Open Access Journals (Sweden)

    Yoed Nissan Kenett

    2013-09-01

    Full Text Available Purpose: Cochlear implants (CIs enable children with severe and profound hearing impairments to perceive the sensation of sound sufficiently to permit oral language acquisition. So far, studies have focused mainly on technological improvements and general outcomes of implantation for speech perception and spoken language development. This study quantitatively explored the semantic networks of children with CIs in comparison to those of age-matched normal hearing (NH peers.Method: Twenty seven children with CIs and twenty seven age- and IQ-matched NH children ages 7-10 were tested on a timed animal verbal fluency task (Name as many animals as you can. The responses were analyzed using correlation and network methodologies. The structure of the animal category semantic networks for both groups were extracted and compared.Results: Children with CIs appeared to have a less-developed semantic lexicon structure compared to age-matched NH peers. The average shortest path length and the network diameter measures were larger for the NH group compared to the CIs group. This difference was consistent for the analysis of networks derived from animal names generated by each group (sample-matched correlation networks and for the networks derived from the common animal names generated by both groups (word-matched correlation networks.Conclusions: The main difference between the semantic networks of children with CIs and NH children lies in the network structure. The semantic network of children with CIs is under-developed compared to the semantic network of the age-matched NH children. We discuss the practical and clinical implications of our findings.

  16. A Framework for Automatic Web Service Discovery Based on Semantics and NLP Techniques

    Directory of Open Access Journals (Sweden)

    Asma Adala

    2011-01-01

    Full Text Available As a greater number of Web Services are made available today, automatic discovery is recognized as an important task. To promote the automation of service discovery, different semantic languages have been created that allow describing the functionality of services in a machine interpretable form using Semantic Web technologies. The problem is that users do not have intimate knowledge about semantic Web service languages and related toolkits. In this paper, we propose a discovery framework that enables semantic Web service discovery based on keywords written in natural language. We describe a novel approach for automatic discovery of semantic Web services which employs Natural Language Processing techniques to match a user request, expressed in natural language, with a semantic Web service description. Additionally, we present an efficient semantic matching technique to compute the semantic distance between ontological concepts.

  17. Diagnostic and prognostic role of semantic processing in preclinical Alzheimer's disease.

    Science.gov (United States)

    Venneri, Annalena; Jahn-Carta, Caroline; Marco, Matteo De; Quaranta, Davide; Marra, Camillo

    2018-06-13

    Relatively spared during most of the timeline of normal aging, semantic memory shows a subtle yet measurable decline even during the pre-clinical stage of Alzheimer's disease. This decline is thought to reflect early neurofibrillary changes and impairment is detectable using tests of language relying on lexical-semantic abilities. A promising approach is the characterization of semantic parameters such as typicality and age of acquisition of words, and propositional density from verbal output. Seminal research like the Nun Study or the analysis of the linguistic decline of famous writers and politicians later diagnosed with Alzheimer's disease supports the early diagnostic value of semantic processing and semantic memory. Moreover, measures of these skills may play an important role for the prognosis of patients with mild cognitive impairment.

  18. Semantics, contrastive linguistics and parallel corpora

    Directory of Open Access Journals (Sweden)

    Violetta Koseska

    2014-09-01

    Full Text Available Semantics, contrastive linguistics and parallel corpora In view of the ambiguity of the term “semantics”, the author shows the differences between the traditional lexical semantics and the contemporary semantics in the light of various semantic schools. She examines semantics differently in connection with contrastive studies where the description must necessary go from the meaning towards the linguistic form, whereas in traditional contrastive studies the description proceeded from the form towards the meaning. This requirement regarding theoretical contrastive studies necessitates construction of a semantic interlanguage, rather than only singling out universal semantic categories expressed with various language means. Such studies can be strongly supported by parallel corpora. However, in order to make them useful for linguists in manual and computer translations, as well as in the development of dictionaries, including online ones, we need not only formal, often automatic, annotation of texts, but also semantic annotation - which is unfortunately manual. In the article we focus on semantic annotation concerning time, aspect and quantification of names and predicates in the whole semantic structure of the sentence on the example of the “Polish-Bulgarian-Russian parallel corpus”.

  19. A Description Of Space Relations In An NLP Model: The ABBYY Compreno Approach

    Directory of Open Access Journals (Sweden)

    Aleksey Leontyev

    2015-12-01

    Full Text Available The current paper is devoted to a formal analysis of the space category and, especially, to questions bound with the presentation of space relations in a formal NLP model. The aim is to demonstrate how linguistic and cognitive problems relating to spatial categorization, definition of spatial entities, and the expression of different locative senses in natural languages can be solved in an artificial intelligence system. We offer a description of the locative groups in the ABBYY Compreno formalism – an integral NLP framework applied for machine translation, semantic search, fact extraction, and other tasks based on the semantic analysis of texts. The model is based on a universal semantic hierarchy of the thesaurus type and includes a description of all possible semantic and syntactic links every word can attach. In this work we define the set of semantic locative relations between words, suggest different tools for their syntactic presentation, give formal restrictions for the word classes that can denote spaces, and show different strategies of dealing with locative prepositions, especially as far as the problem of their machine translation is concerned.

  20. Adaptive semantics visualization

    CERN Document Server

    Nazemi, Kawa

    2016-01-01

    This book introduces a novel approach for intelligent visualizations that adapts the different visual variables and data processing to human’s behavior and given tasks. Thereby a number of new algorithms and methods are introduced to satisfy the human need of information and knowledge and enable a usable and attractive way of information acquisition. Each method and algorithm is illustrated in a replicable way to enable the reproduction of the entire “SemaVis” system or parts of it. The introduced evaluation is scientifically well-designed and performed with more than enough participants to validate the benefits of the methods. Beside the introduced new approaches and algorithms, readers may find a sophisticated literature review in Information Visualization and Visual Analytics, Semantics and information extraction, and intelligent and adaptive systems. This book is based on an awarded and distinguished doctoral thesis in computer science.

  1. Task choice and semantic interference in picture naming

    OpenAIRE

    Piai, V.; Roelofs, A.P.A.; Schriefers, H.J.

    2015-01-01

    Evidence from dual-task performance indicates that speakers prefer not to select simultaneous responses in picture naming and another unrelated task, suggesting a response selection bottleneck in naming. In particular, when participants respond to tones with a manual response and name pictures with superimposed semantically related or unrelated distractor words, semantic interference in naming tends to be constant across stimulus onset asynchronies (SOAs) between the tone stimulus and the pic...

  2. Behavioural and electrophysiological effects related to semantic violations during braille reading.

    Science.gov (United States)

    Glyn, Vania; Lim, Vanessa K; Hamm, Jeff P; Mathur, Ashwin; Hughes, Barry

    2015-10-01

    This study investigated the potential to detect event related potentials (ERPs) occurring in response to a specific task in braille reading. This would expand current methodologies for studying the cognitive processes underlying braille reading. An N400 effect paradigm was utilised, whereby proficient blind braille readers read congruent- and incongruent-ending braille sentences. Kinematic and electroencephalography (EEG) data were obtained simultaneously and synchronised. The ERPs differed between the incongruent and congruent sentences in a manner consistent with the N400 effect found with a previous sighted reading paradigm, demonstrating that ERPs can be obtained during braille reading. The frequency of finger reversals and the degree of intermittency in the finger velocity were significantly higher when reading incongruent versus congruent sentence endings. Both reversals and the potential N400 effect may reflect processes involved in semantic unification. These findings have significant implications for the modelling of braille reading. The refinement of the technique will enable other ERPs to be identified and related to behavioural responses, to further our understanding of the braille reading process. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Is Semantic Priming (Ir)rational? Insights from the Speeded Word Fragment Completion Task

    Science.gov (United States)

    Heyman, Tom; Hutchison, Keith A.; Storms, Gert

    2016-01-01

    Semantic priming, the phenomenon that a target is recognized faster if it is preceded by a semantically related prime, is a well-established effect. However, the mechanisms producing semantic priming are subject of debate. Several theories assume that the underlying processes are controllable and tuned to prime utility. In contrast, purely…

  4. Personal semantics: Is it distinct from episodic and semantic memory? An electrophysiological study of memory for autobiographical facts and repeated events in honor of Shlomo Bentin.

    Science.gov (United States)

    Renoult, Louis; Tanguay, Annick; Beaudry, Myriam; Tavakoli, Paniz; Rabipour, Sheida; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian; Davidson, Patrick S R

    2016-03-01

    Declarative memory is thought to consist of two independent systems: episodic and semantic. Episodic memory represents personal and contextually unique events, while semantic memory represents culturally-shared, acontextual factual knowledge. Personal semantics refers to aspects of declarative memory that appear to fall somewhere in between the extremes of episodic and semantic. Examples include autobiographical knowledge and memories of repeated personal events. These two aspects of personal semantics have been studied little and rarely compared to both semantic and episodic memory. We recorded the event-related potentials (ERPs) of 27 healthy participants while they verified the veracity of sentences probing four types of questions: general (i.e., semantic) facts, autobiographical facts, repeated events, and unique (i.e., episodic) events. Behavioral results showed equivalent reaction times in all 4 conditions. True sentences were verified faster than false sentences, except for unique events for which no significant difference was observed. Electrophysiological results showed that the N400 (which is classically associated with retrieval from semantic memory) was maximal for general facts and the LPC (which is classically associated with retrieval from episodic memory) was maximal for unique events. For both ERP components, the two personal semantic conditions (i.e., autobiographical facts and repeated events) systematically differed from semantic memory. In addition, N400 amplitudes also differentiated autobiographical facts from unique events. Autobiographical facts and repeated events did not differ significantly from each other but their corresponding scalp distributions differed from those associated with general facts. Our results suggest that the neural correlates of personal semantics can be distinguished from those of semantic and episodic memory, and may provide clues as to how unique events are transformed to semantic memory. Copyright © 2015 Elsevier

  5. The semantic network, lexical access, and reading comprehension in monolingual and bilingual children : An individual differences study

    NARCIS (Netherlands)

    Spätgens, T.; Schoonen, R.

    Using a semantic priming experiment, the influence of lexical access and knowledge of semantic relations on reading comprehension was studied in Dutch monolingual and bilingual minority children. Both context-independent semantic relations in the form of category coordinates and context-dependent

  6. Semantic web for dummies

    CERN Document Server

    Pollock, Jeffrey T

    2009-01-01

    Semantic Web technology is already changing how we interact with data on the Web. By connecting random information on the Internet in new ways, Web 3.0, as it is sometimes called, represents an exciting online evolution. Whether you're a consumer doing research online, a business owner who wants to offer your customers the most useful Web site, or an IT manager eager to understand Semantic Web solutions, Semantic Web For Dummies is the place to start! It will help you:Know how the typical Internet user will recognize the effects of the Semantic WebExplore all the benefits the data Web offers t

  7. Jigsaw Semantics

    Directory of Open Access Journals (Sweden)

    Paul J. E. Dekker

    2010-12-01

    .http://dx.doi.org/10.1023/A:1017575313451Dekker, Paul. 2004. ‘Grounding Dynamic Semantics’. In Anne Bezuidenhout & Marga Reimer (eds. ‘Descriptions and Beyond: An Interdisciplinary Collection of Essays on Definite and Indefinite Descriptions and other Related Phenomena’, Oxford: Oxford University Press.Dekker, Paul. 2007. ‘Optimal Inquisitive Discourse’. In Maria Aloni, Alastair Butler & Paul Dekker (eds. ‘Questions in Dynamic Semantics’, CRiSPI 17, pp. 83–101. Amsterdam: Elsevier.Frege, Gottlob. 1892. ‘Über Sinn und Bedeutung’. Zeitschrift für Philosophie und philosophische Kritik NF 100: pp. 25–50.Ginzburg, Jonathan. 1995. ‘Resolving Questions, I & II’. Linguistics and Philosophy 18, no. 5,6: pp. 459–527 and 567–609.Ginzburg, Jonathan. To appear. The Interactive Stance: Meaning for Conversation. Oxford: Oxford University Press.Groenendijk, Jeroen. 1999. ‘The Logic of Interrogation’. In T. Matthews & D. Strolovitch (eds. ‘Proceedings of SALT IX’, Also appeared in Aloni, M., Butler, A., and Dekker, P., 2007, Questions in Dynamic Semantics, CRiSPI, Elsevier.: CLC Publications.Groenendijk, Jeroen & Roelofsen, Floris. 2009. ‘Inquisitive Semantics and Pragmatics’. In Jesus M. Larrazabal & Larraitz Zubeldia (eds. ‘Meaning, Content, and Argument: Proceedings of the ILCLI International Workshop on Semantics, Pragmatics, and Rhetoric’, Bilbao: University of the Basque Country Press.Groenendijk, Jeroen & Stokhof, Martin. 1991. ‘Dynamic Predicate Logic’. Linguistics and Philosophy 14, no. 1: pp. 39–100.http://dx.doi.org/10.1007/BF00628304Hulstijn, Joris. 1997. ‘Structured Information States. Raising and Resolving Issues’. In Anton Benz & Gerhard Jäger (eds. ‘Proceedings of MunDial97’, pp. 99–117. University of Munich.Jäger, Gerhard. 1996. ‘Only Updates. On the Dynamics of the Focus Particle only’. In Martin Stokhof & Paul Dekker (eds. ‘Proceedings of the Tenth Amsterdam Colloquium’, pp. 387–405

  8. Book review of Yoad Winter’s Elements of formal semantics (2016

    Directory of Open Access Journals (Sweden)

    Jessica Rett

    2016-10-01

    Full Text Available Yoad Winter’s (2016 new textbook, 'Elements of formal semantics', is a formally sophisticated introduction to semantic theory. It treats standard beginner topics (e.g. transitivity, quantifiers, relative clauses carefully and efficiently, using a directly compositional lambda calculus.

  9. Intuitions and Competence in Formal Semantics

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    Martin Stokhof

    2010-12-01

    Full Text Available In formal semantics intuition plays a key role, in two ways. Intuitions about semantic properties of expressions are the primary data, and intuitions of the semanticists are the main access to these data. The paper investigates how this dual role is related to the concept of competence and the role that this concept plays in semantics. And it inquires whether the self-reflexive role of intuitions has consequences for the methodology of semantics as an empirical discipline.ReferencesBaggio, Giosuè, van Lambalgen, Michiel & Hagoort, Peter. 2008. ‘Computing and recomputing discourse models: an ERP study of the semantics of temporal connectives’. Journal of Memory and Language 59, no. 1: 36–53.http://dx.doi.org/10.1016/j.jml.2008.02.005Chierchia, Gennaro & McConnell-Ginet, Sally. 2000. Meaning and Grammar. second ed. Cambridge, Mass.: MIT Press.Chomsky, Noam. 1965. Aspects of the Theory of Syntax. Cambridge, Mass.: MIT Press.Cresswell, Max J. 1978. ‘Semantic competence’. In F. Guenthner & M. Guenther-Reutter (eds. ‘Meaning and Translation’, 9–27. Duckworth, London. de Swart, Henriëtte. 1998. Introduction to Natural Language Semantics. Stanford: CSLI.Dowty, David, Wall, Robert & Peters, Stanley. 1981. Introduction to Montague Semantics. Dordrecht: Reidel.Heim, Irene & Kratzer, Angelika. 1998. Semantics in Generative Grammar. Oxford: Blackwell.Larson, Richard & Segal, Gabriel. 1995. Knowledge of Meaning. Cambridge, Mass.: MIT Press.Lewis, David K. 1975. ‘Languages and Language’. In Keith Gunderson (ed. ‘Language, Mind and Knowledge’, 3–35. Minneapolis: University of Minnesota Press.Montague, Richard. 1970. ‘Universal Grammar’. Theoria 36: 373–98.http://dx.doi.org/10.1111/j.1755-2567.1970.tb00434.xPartee, Barbara H. 1979. ‘Semantics – Mathematics or Psychology?’ In Rainer Bäuerle, Urs Egli & Arnim von Stechow (eds. ‘Semantics from Different Points of View’, 1–14. Berlin: Springer.Partee, Barbara H. 1980.

  10. A Semantic Approach to Cross-Disciplinary Research Collaboration

    Directory of Open Access Journals (Sweden)

    Laurens De Vocht

    2012-11-01

    Full Text Available The latest developments in ICT, more specifically Social Media and Web 2.0 tools, facilitate the use of online services in research and education. This is also known as Research 2.0 and Technology Enhanced Learning. Web 2.0 tools are especially useful in cases where experts from different disciplines want to collaborate. We suggest an integrated method that embeds these services in research and learning processes, because it is a laborious task for researchers and learners to check and use all varying types of tools and services. We explain a flexible model that uses state-of-the-art semantic technologies to model both structured and unstructured research data. The research data is extracted from many online resources and Social Media. We implement learning objects as an abstraction of the semantically modeled research data. We propose an environment that improves the scientific research and learning process by allowing researchers to efficiently browse the information and concepts represented as learning objects.

  11. Using Local Grammar for Entity Extraction from Clinical Reports

    Directory of Open Access Journals (Sweden)

    Aicha Ghoulam

    2015-06-01

    Full Text Available Information Extraction (IE is a natural language processing (NLP task whose aim is to analyze texts written in natural language to extract structured and useful information such as named entities and semantic relations linking these entities. Information extraction is an important task for many applications such as bio-medical literature mining, customer care, community websites, and personal information management. The increasing information available in patient clinical reports is difficult to access. As it is often in an unstructured text form, doctors need tools to enable them access to this information and the ability to search it. Hence, a system for extracting this information in a structured form can benefits healthcare professionals. The work presented in this paper uses a local grammar approach to extract medical named entities from French patient clinical reports. Experimental results show that the proposed approach achieved an F-Measure of 90. 06%.

  12. Altered Neural Activity during Semantic Object Memory Retrieval in Amnestic Mild Cognitive Impairment as Measured by Event-Related Potentials.

    Science.gov (United States)

    Chiang, Hsueh-Sheng; Mudar, Raksha A; Pudhiyidath, Athula; Spence, Jeffrey S; Womack, Kyle B; Cullum, C Munro; Tanner, Jeremy A; Eroh, Justin; Kraut, Michael A; Hart, John

    2015-01-01

    Deficits in semantic memory in individuals with amnestic mild cognitive impairment (aMCI) have been previously reported, but the underlying neurobiological mechanisms remain to be clarified. We examined event-related potentials (ERPs) associated with semantic memory retrieval in 16 individuals with aMCI as compared to 17 normal controls using the Semantic Object Retrieval Task (EEG SORT). In this task, subjects judged whether pairs of words (object features) elicited retrieval of an object (retrieval trials) or not (non-retrieval trials). Behavioral findings revealed that aMCI subjects had lower accuracy scores and marginally longer reaction time compared to controls. We used a multivariate analytical technique (STAT-PCA) to investigate similarities and differences in ERPs between aMCI and control groups. STAT-PCA revealed a left fronto-temporal component starting at around 750 ms post-stimulus in both groups. However, unlike controls, aMCI subjects showed an increase in the frontal-parietal scalp potential that distinguished retrieval from non-retrieval trials between 950 and 1050 ms post-stimulus negatively correlated with the performance on the logical memory subtest of the Wechsler Memory Scale-III. Thus, individuals with aMCI were not only impaired in their behavioral performance on SORT relative to controls, but also displayed alteration in the corresponding ERPs. The altered neural activity in aMCI compared to controls suggests a more sustained and effortful search during object memory retrieval, which may be a potential marker indicating disease processes at the pre-dementia stage.

  13. The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction.

    Science.gov (United States)

    Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A; Barak, Ohr; Lambon Ralph, Matthew A; Jefferies, Elizabeth

    2018-01-03

    Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., , Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal 'hub' in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive-semantic goal representations, largely supported by executive regions such as frontal and parietal cortex, are thought to allow the generation of non-dominant aspects of knowledge when these are appropriate for the task or context. Semantic aphasia (SA) patients have executive-semantic deficits, and these are correlated with general executive impairment. If the CSC proposal is correct, patients with executive impairment should not only exhibit impaired semantic cognition, but should also show characteristics that align with those observed in SA. This possibility remains largely untested, as patients selected on the basis that they show executive impairment (i.e., with 'dysexecutive syndrome') have not been extensively tested on tasks tapping semantic control and have not been previously compared with SA cases. We explored conceptual processing in 12 patients showing symptoms consistent with dysexecutive syndrome (DYS) and 24 SA patients, using a range of multimodal semantic assessments which manipulated control demands. Patients with executive impairments, despite not being selected to show semantic impairments, nevertheless showed parallel patterns to SA cases. They showed strong effects of distractor strength, cues and miscues, and probe-target distance, plus minimal effects of word frequency on comprehension (unlike semantic dementia patients with degradation of conceptual knowledge). This supports a component process account of semantic cognition in which retrieval is shaped by control processes, and confirms that deficits in SA patients reflect

  14. Functional heterogeneity within the default network during semantic processing and speech production.

    Directory of Open Access Journals (Sweden)

    Mohamed L Seghier

    2012-08-01

    Full Text Available This fMRI study investigated the functional heterogeneity of the core nodes of the default mode network (DMN during language processing. The core nodes of the DMN were defined as task-induced deactivations over multiple tasks in 94 healthy subjects. We used a factorial design that manipulated different tasks (semantic matching or speech production and stimuli (familiar words and objects or unfamiliar stimuli, alternating with periods of fixation/rest. Our findings revealed several consistent effects in the DMN, namely less deactivations in the left inferior parietal lobule during semantic than perceptual matching in parallel with greater deactivations during semantic matching in anterior subdivisions of the posterior cingulate cortex and the ventromedial prefrontal cortex. This suggests that, when the brain is engaged in effortful semantic tasks, a part of the DMN in the left angular gyrus was less deactivated as five other nodes of the DMN were more deactivated. These five DMN areas, where deactivation was greater for semantic than perceptual matching, were further differentiated because deactivation was greater in (i posterior ventromedial prefrontal cortex for speech production relative to semantic matching, (ii posterior precuneus and posterior cingulate cortex for perceptual processing relative to speech production and (iii right inferior parietal cortex for pictures of objects relative to written words during both naming and semantic decisions. Our results thus highlight that task difficulty alone cannot fully explain the functional variability in task-induced deactivations. Together these results emphasize that core nodes within the DMN are functionally heterogeneous and differentially sensitive to the type of language processing.

  15. Putting semantics into the semantic web: how well can it capture biology?

    Science.gov (United States)

    Kazic, Toni

    2006-01-01

    Could the Semantic Web work for computations of biological interest in the way it's intended to work for movie reviews and commercial transactions? It would be wonderful if it could, so it's worth looking to see if its infrastructure is adequate to the job. The technologies of the Semantic Web make several crucial assumptions. I examine those assumptions; argue that they create significant problems; and suggest some alternative ways of achieving the Semantic Web's goals for biology.

  16. The Effect of Semantic Mapping on Reading Comprehension

    Directory of Open Access Journals (Sweden)

    Elmira Taghavi

    2008-11-01

    Full Text Available The research reported here examined the relative effectiveness of semantic mapping, as an interactive pre-reading strategy, on reading comprehension of Iranian undergraduate students (non-EFL majors. It also examined whether there was an interaction between gender and the effect of teaching semantic mapping strategy on reading comprehension. The participants in this study consisted of 120 male and female pre-intermediate undergraduate students taking a General English course at UrmiaUniversity in Spring 2008. A Certificate of Advanced English Reading Paper (CAE was administered to measure the students’ proficiency at the beginning of the research. Later, the participants were semi-randomly (Mackey and Gass, 2005 assigned into experimental and control groups. The experimental group was instructed on how toemploy semantic mapping strategy in reading while the control group received normal reading instruction. The post-test results supported the findings of earlier research that instruction on the application of semantic mapping contributed to reading comprehension. Further findings and implications are discussed in the paper.

  17. The roles of scene gist and spatial dependency among objects in the semantic guidance of attention in real-world scenes.

    Science.gov (United States)

    Wu, Chia-Chien; Wang, Hsueh-Cheng; Pomplun, Marc

    2014-12-01

    A previous study (Vision Research 51 (2011) 1192-1205) found evidence for semantic guidance of visual attention during the inspection of real-world scenes, i.e., an influence of semantic relationships among scene objects on overt shifts of attention. In particular, the results revealed an observer bias toward gaze transitions between semantically similar objects. However, this effect is not necessarily indicative of semantic processing of individual objects but may be mediated by knowledge of the scene gist, which does not require object recognition, or by known spatial dependency among objects. To examine the mechanisms underlying semantic guidance, in the present study, participants were asked to view a series of displays with the scene gist excluded and spatial dependency varied. Our results show that spatial dependency among objects seems to be sufficient to induce semantic guidance. Scene gist, on the other hand, does not seem to affect how observers use semantic information to guide attention while viewing natural scenes. Extracting semantic information mainly based on spatial dependency may be an efficient strategy of the visual system that only adds little cognitive load to the viewing task. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Semantically Induced Distortions of Visual Awareness in a Patient with Balint's Syndrome

    Science.gov (United States)

    Soto, David; Humphreys, Glyn W.

    2009-01-01

    We present data indicating that visual awareness for a basic perceptual feature (colour) can be influenced by the relation between the feature and the semantic properties of the stimulus. We examined semantic interference from the meaning of a colour word ("RED") on simple colour (ink related) detection responses in a patient with simultagnosia…

  19. Challenges as enablers for high quality Linked Data: insights from the Semantic Publishing Challenge

    Directory of Open Access Journals (Sweden)

    Anastasia Dimou

    2017-01-01

    Full Text Available While most challenges organized so far in the Semantic Web domain are focused on comparing tools with respect to different criteria such as their features and competencies, or exploiting semantically enriched data, the Semantic Web Evaluation Challenges series, co-located with the ESWC Semantic Web Conference, aims to compare them based on their output, namely the produced dataset. The Semantic Publishing Challenge is one of these challenges. Its goal is to involve participants in extracting data from heterogeneous sources on scholarly publications, and producing Linked Data that can be exploited by the community itself. This paper reviews lessons learned from both (i the overall organization of the Semantic Publishing Challenge, regarding the definition of the tasks, building the input dataset and forming the evaluation, and (ii the results produced by the participants, regarding the proposed approaches, the used tools, the preferred vocabularies and the results produced in the three editions of 2014, 2015 and 2016. We compared these lessons to other Semantic Web Evaluation Challenges. In this paper, we (i distill best practices for organizing such challenges that could be applied to similar events, and (ii report observations on Linked Data publishing derived from the submitted solutions. We conclude that higher quality may be achieved when Linked Data is produced as a result of a challenge, because the competition becomes an incentive, while solutions become better with respect to Linked Data publishing best practices when they are evaluated against the rules of the  challenge.

  20. Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

    DEFF Research Database (Denmark)

    Danvy, Olivier

    2008-01-01

    We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fuse...... its transition function with its driver loop, obtaining the functional implementation of a big-step abstract machine; (2) we adjust this big-step abstract machine so that it is in defunctionalized form, obtaining the functional implementation of a second big-step abstract machine; (3) we...... refunctionalize this adjusted abstract machine, obtaining the functional implementation of a natural semantics in continuation style; and (4) we closure-unconvert this natural semantics, obtaining a compositional continuation-passing evaluation function which we identify as the functional implementation...

  1. Are there mental lexicons? The role of semantics in lexical decision.

    Science.gov (United States)

    Dilkina, Katia; McClelland, James L; Plaut, David C

    2010-12-13

    What is the underlying representation of lexical knowledge? How do we know whether a given string of letters is a word, whereas another string of letters is not? There are two competing models of lexical processing in the literature. The first proposes that we rely on mental lexicons. The second claims there are no mental lexicons; we identify certain items as words based on semantic knowledge. Thus, the former approach - the multiple-systems view - posits that lexical and semantic processing are subserved by separate systems, whereas the latter approach - the single-system view - holds that the two are interdependent. Semantic dementia patients, who have a cross-modal semantic impairment, show an accompanying and related lexical deficit. These findings support the single-system approach. However, a report of an SD patient whose impairment on lexical decision was not related to his semantic deficits in item-specific ways has presented a challenge to this view. If the two types of processing rely on a common system, then shouldn't damage impair the same items on all tasks? We present a single-system model of lexical and semantic processing, where there are no lexicons, and performance on lexical decision involves the activation of semantic representations. We show how, when these representations are damaged, accuracy on semantic and lexical tasks falls off together, but not necessarily on the same set of items. These findings are congruent with the patient data. We provide an explicit explanation of this pattern of results in our model, by defining and measuring the effects of two orthogonal factors - spelling consistency and concept consistency. Copyright © 2010 Elsevier B.V. All rights reserved.

  2. Temporal Representation in Semantic Graphs

    Energy Technology Data Exchange (ETDEWEB)

    Levandoski, J J; Abdulla, G M

    2007-08-07

    A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.

  3. Flow Logics and Operational Semantics

    DEFF Research Database (Denmark)

    Nielson, Flemming; Nielson, Hanne Riis

    1998-01-01

    Flow logic is a “fast prototyping” approach to program analysis that shows great promise of being able to deal with a wide variety of languages and calculi for computation. However, seemingly innocent choices in the flow logic as well as in the operational semantics may inhibit proving the analys...... correct. Our main conclusion is that environment based semantics is more flexible than either substitution based semantics or semantics making use of structural congruences (like alpha-renaming)....

  4. Semantic Versus Syntactic Cutting Planes

    OpenAIRE

    Filmus, Yuval; Hrubeš, Pavel; Lauria, Massimo

    2016-01-01

    In this paper, we compare the strength of the semantic and syntactic version of the cutting planes proof system. First, we show that the lower bound technique of Pudlák applies also to semantic cutting planes: the proof system has feasible interpolation via monotone real circuits, which gives an exponential lower bound on lengths of semantic cutting planes refutations. Second, we show that semantic refutations are stronger than syntactic ones. In particular, we give a formula for whic...

  5. An fMRI study of semantic processing in men with schizophrenia

    Science.gov (United States)

    Kubicki, M.; McCarley, R.W.; Nestor, P.G.; Huh, T.; Kikinis, R.; Shenton, M.E.; Wible, C.G.

    2009-01-01

    As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus

  6. An fMRI study of semantic processing in men with schizophrenia.

    Science.gov (United States)

    Kubicki, M; McCarley, R W; Nestor, P G; Huh, T; Kikinis, R; Shenton, M E; Wible, C G

    2003-12-01

    As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus

  7. Semantic word category processing in semantic dementia and posterior cortical atrophy.

    Science.gov (United States)

    Shebani, Zubaida; Patterson, Karalyn; Nestor, Peter J; Diaz-de-Grenu, Lara Z; Dawson, Kate; Pulvermüller, Friedemann

    2017-08-01

    There is general agreement that perisylvian language cortex plays a major role in lexical and semantic processing; but the contribution of additional, more widespread, brain areas in the processing of different semantic word categories remains controversial. We investigated word processing in two groups of patients whose neurodegenerative diseases preferentially affect specific parts of the brain, to determine whether their performance would vary as a function of semantic categories proposed to recruit those brain regions. Cohorts with (i) Semantic Dementia (SD), who have anterior temporal-lobe atrophy, and (ii) Posterior Cortical Atrophy (PCA), who have predominantly parieto-occipital atrophy, performed a lexical decision test on words from five different lexico-semantic categories: colour (e.g., yellow), form (oval), number (seven), spatial prepositions (under) and function words (also). Sets of pseudo-word foils matched the target words in length and bi-/tri-gram frequency. Word-frequency was matched between the two visual word categories (colour and form) and across the three other categories (number, prepositions, and function words). Age-matched healthy individuals served as controls. Although broad word processing deficits were apparent in both patient groups, the deficit was strongest for colour words in SD and for spatial prepositions in PCA. The patterns of performance on the lexical decision task demonstrate (a) general lexicosemantic processing deficits in both groups, though more prominent in SD than in PCA, and (b) differential involvement of anterior-temporal and posterior-parietal cortex in the processing of specific semantic categories of words. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. The effects of gender and self-insight on early semantic processing.

    Directory of Open Access Journals (Sweden)

    Xu Xu

    Full Text Available This event-related potential (ERP study explored individual differences associated with gender and level of self-insight in early semantic processing. Forty-eight Chinese native speakers completed a semantic judgment task with three different categories of words: abstract neutral words (e.g., logic, effect, concrete neutral words (e.g., teapot, table, and emotion words (e.g., despair, guilt. They then assessed their levels of self-insight. Results showed that women engaged in greater processing than did men. Gender differences also manifested in the relationship between level of self-insight and word processing. For women, level of self-insight was associated with level of semantic activation for emotion words and abstract neutral words, but not for concrete neutral words. For men, level of self-insight was related to processing speed, particularly in response to abstract and concrete neutral words. These findings provide electrophysiological evidence for the effects of gender and self-insight on semantic processing and highlight the need to take into consideration subject variables in related research.

  9. Response-related potentials during semantic priming: the effect of a speeded button response task on ERPs.

    Directory of Open Access Journals (Sweden)

    Marijn van Vliet

    Full Text Available This study examines the influence of a button response task on the event-related potential (ERP in a semantic priming experiment. Of particular interest is the N400 component. In many semantic priming studies, subjects are asked to respond to a stimulus as fast and accurately as possible by pressing a button. Response time (RT is recorded in parallel with an electroencephalogram (EEG for ERP analysis. In this case, the response occurs in the time window used for ERP analysis and response-related components may overlap with stimulus-locked ones such as the N400. This has led to a recommendation against such a design, although the issue has not been explored in depth. Since studies keep being published that disregard this issue, a more detailed examination of influence of response-related potentials on the ERP is needed. Two experiments were performed in which subjects pressed one of two buttons with their dominant hand in response to word-pairs with varying association strength (AS, indicating a personal judgement of association between the two words. In the first experiment, subjects were instructed to respond as fast and accurately as possible. In the second experiment, subjects delayed their button response to enforce a one second interval between the onset of the target word and the button response. Results show that in the first experiment a P3 component and motor-related potentials (MRPs overlap with the N400 component, which can cause a misinterpretation of the latter. In order to study the N400 component, the button response should be delayed to avoid contamination of the ERP with response-related components.

  10. Uncovering highly obfuscated plagiarism cases using fuzzy semantic-based similarity model

    Directory of Open Access Journals (Sweden)

    Salha M. Alzahrani

    2015-07-01

    Full Text Available Highly obfuscated plagiarism cases contain unseen and obfuscated texts, which pose difficulties when using existing plagiarism detection methods. A fuzzy semantic-based similarity model for uncovering obfuscated plagiarism is presented and compared with five state-of-the-art baselines. Semantic relatedness between words is studied based on the part-of-speech (POS tags and WordNet-based similarity measures. Fuzzy-based rules are introduced to assess the semantic distance between source and suspicious texts of short lengths, which implement the semantic relatedness between words as a membership function to a fuzzy set. In order to minimize the number of false positives and false negatives, a learning method that combines a permission threshold and a variation threshold is used to decide true plagiarism cases. The proposed model and the baselines are evaluated on 99,033 ground-truth annotated cases extracted from different datasets, including 11,621 (11.7% handmade paraphrases, 54,815 (55.4% artificial plagiarism cases, and 32,578 (32.9% plagiarism-free cases. We conduct extensive experimental verifications, including the study of the effects of different segmentations schemes and parameter settings. Results are assessed using precision, recall, F-measure and granularity on stratified 10-fold cross-validation data. The statistical analysis using paired t-tests shows that the proposed approach is statistically significant in comparison with the baselines, which demonstrates the competence of fuzzy semantic-based model to detect plagiarism cases beyond the literal plagiarism. Additionally, the analysis of variance (ANOVA statistical test shows the effectiveness of different segmentation schemes used with the proposed approach.

  11. Semantic encoding and retrieval in the left inferior prefrontal cortex: a functional MRI study of task difficulty and process specificity.

    Science.gov (United States)

    Demb, J B; Desmond, J E; Wagner, A D; Vaidya, C J; Glover, G H; Gabrieli, J D

    1995-09-01

    Prefrontal cortical function was examined during semantic encoding and repetition priming using functional magnetic resonance imaging (fMRI), a noninvasive technique for localizing regional changes in blood oxygenation, a correlate of neural activity. Words studied in a semantic (deep) encoding condition were better remembered than words studied in both easier and more difficult nonsemantic (shallow) encoding conditions, with difficulty indexed by response time. The left inferior prefrontal cortex (LIPC) (Brodmann's areas 45, 46, 47) showed increased activation during semantic encoding relative to nonsemantic encoding regardless of the relative difficulty of the nonsemantic encoding task. Therefore, LIPC activation appears to be related to semantic encoding and not task difficulty. Semantic encoding decisions are performed faster the second time words are presented. This represents semantic repetition priming, a facilitation in semantic processing for previously encoded words that is not dependent on intentional recollection. The same LIPC area activated during semantic encoding showed decreased activation during repeated semantic encoding relative to initial semantic encoding of the same words. This decrease in activation during repeated encoding was process specific; it occurred when words were semantically reprocessed but not when words were nonsemantically reprocessed. The results were apparent in both individual and averaged functional maps. These findings suggest that the LIPC is part of a semantic executive system that contributes to the on-line retrieval of semantic information.

  12. The modulating effect of education on semantic interference during healthy aging.

    Directory of Open Access Journals (Sweden)

    Daniela Paolieri

    Full Text Available Aging has traditionally been related to impairments in name retrieval. These impairments have usually been explained by a phonological transmission deficit hypothesis or by an inhibitory deficit hypothesis. This decline can, however, be modulated by the educational level of the sample. This study analyzed the possible role of these approaches in explaining both object and face naming impairments during aging. Older adults with low and high educational level and young adults with high educational level were asked to repeatedly name objects or famous people using the semantic-blocking paradigm. We compared naming when exemplars were presented in a semantically homogeneous or in a semantically heterogeneous context. Results revealed significantly slower rates of both face and object naming in the homogeneous context (i.e., semantic interference, with a stronger effect for face naming. Interestingly, the group of older adults with a lower educational level showed an increased semantic interference effect during face naming. These findings suggest the joint work of the two mechanisms proposed to explain age-related naming difficulties, i.e., the inhibitory deficit and the transmission deficit hypothesis. Therefore, the stronger vulnerability to semantic interference in the lower educated older adult sample would possibly point to a failure in the inhibitory mechanisms in charge of interference resolution, as proposed by the inhibitory deficit hypothesis. In addition, the fact that this interference effect was mainly restricted to face naming and not to object naming would be consistent with the increased age-related difficulties during proper name retrieval, as suggested by the transmission deficit hypothesis.

  13. The modulating effect of education on semantic interference during healthy aging.

    Science.gov (United States)

    Paolieri, Daniela; Marful, Alejandra; Morales, Luis; Bajo, María Teresa

    2018-01-01

    Aging has traditionally been related to impairments in name retrieval. These impairments have usually been explained by a phonological transmission deficit hypothesis or by an inhibitory deficit hypothesis. This decline can, however, be modulated by the educational level of the sample. This study analyzed the possible role of these approaches in explaining both object and face naming impairments during aging. Older adults with low and high educational level and young adults with high educational level were asked to repeatedly name objects or famous people using the semantic-blocking paradigm. We compared naming when exemplars were presented in a semantically homogeneous or in a semantically heterogeneous context. Results revealed significantly slower rates of both face and object naming in the homogeneous context (i.e., semantic interference), with a stronger effect for face naming. Interestingly, the group of older adults with a lower educational level showed an increased semantic interference effect during face naming. These findings suggest the joint work of the two mechanisms proposed to explain age-related naming difficulties, i.e., the inhibitory deficit and the transmission deficit hypothesis. Therefore, the stronger vulnerability to semantic interference in the lower educated older adult sample would possibly point to a failure in the inhibitory mechanisms in charge of interference resolution, as proposed by the inhibitory deficit hypothesis. In addition, the fact that this interference effect was mainly restricted to face naming and not to object naming would be consistent with the increased age-related difficulties during proper name retrieval, as suggested by the transmission deficit hypothesis.

  14. Ant-based extraction of rules in simple decision systems over ontological graphs

    Directory of Open Access Journals (Sweden)

    Pancerz Krzysztof

    2015-06-01

    Full Text Available In the paper, the problem of extraction of complex decision rules in simple decision systems over ontological graphs is considered. The extracted rules are consistent with the dominance principle similar to that applied in the dominancebased rough set approach (DRSA. In our study, we propose to use a heuristic algorithm, utilizing the ant-based clustering approach, searching the semantic spaces of concepts presented by means of ontological graphs. Concepts included in the semantic spaces are values of attributes describing objects in simple decision systems

  15. Anterior temporal cortex and semantic memory: reconciling findings from neuropsychology and functional imaging.

    Science.gov (United States)

    Rogers, Timothy T; Hocking, Julia; Noppeney, Uta; Mechelli, Andrea; Gorno-Tempini, Maria Luisa; Patterson, Karalyn; Price, Cathy J

    2006-09-01

    Studies of semantic impairment arising from brain disease suggest that the anterior temporal lobes are critical for semantic abilities in humans; yet activation of these regions is rarely reported in functional imaging studies of healthy controls performing semantic tasks. Here, we combined neuropsychological and PET functional imaging data to show that when healthy subjects identify concepts at a specific level, the regions activated correspond to the site of maximal atrophy in patients with relatively pure semantic impairment. The stimuli were color photographs of common animals or vehicles, and the task was category verification at specific (e.g., robin), intermediate (e.g., bird), or general (e.g., animal) levels. Specific, relative to general, categorization activated the antero-lateral temporal cortices bilaterally, despite matching of these experimental conditions for difficulty. Critically, in patients with atrophy in precisely these areas, the most pronounced deficit was in the retrieval of specific semantic information.

  16. SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

    Science.gov (United States)

    Patton, Evan W.; Seyed, Patrice; Wang, Ping; Fu, Linyun; Dein, F. Joshua; Bristol, R. Sky; McGuinness, Deborah L.

    2014-01-01

    We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

  17. Context effects in embodied lexical-semantic processing

    Directory of Open Access Journals (Sweden)

    Wessel O Van Dam

    2010-10-01

    Full Text Available The embodied view of language comprehension proposes that the meaning of words is grounded in perception and action rather than represented in abstract amodal symbols. Support for embodied theories of language processing comes from behavioural studies showing that understanding a sentence about an action can modulate congruent and incongruent physical responses, suggesting motor involvement during comprehension of sentences referring to bodily movement. Additionally, several neuroimaging studies have provided evidence that comprehending single words denoting manipulable objects elicits specific responses in the neural motor system. An interesting question that remains is whether action semantic knowledge is directly activated as motor simulations in the brain, or rather modulated by the semantic context in which action words are encountered. In the current paper we investigated the nature of conceptual representations using a go/no-go lexical decision task. Specifically, target words were either presented in a semantic context that emphasized dominant action features (features related to the functional use of an object or non-dominant action features. The response latencies in a lexical decision task reveal that participants were faster to respond to words denoting objects for which the functional use was congruent with the prepared movement. This facilitation effect, however, was only apparent when the semantic context emphasized corresponding motor properties. These findings suggest that motor involvement during comprehension of sentences is not automatic. Rather, the results suggest that conceptual processing is a context-dependent process that incorporates motor-related knowledge in a flexible manner.

  18. Semantic Web Primer

    NARCIS (Netherlands)

    Antoniou, Grigoris; Harmelen, Frank van

    2004-01-01

    The development of the Semantic Web, with machine-readable content, has the potential to revolutionize the World Wide Web and its use. A Semantic Web Primer provides an introduction and guide to this still emerging field, describing its key ideas, languages, and technologies. Suitable for use as a

  19. The autonomy of grammar and semantic internalism

    Directory of Open Access Journals (Sweden)

    Dobler Tamara

    2014-01-01

    Full Text Available In his post-Tractatus work on natural language use, Wittgenstein defended the notion of what he dubbed the autonomy of grammar. According to this thought, grammar - or semantics, in a more recent idiom - is essentially autonomous from metaphysical considerations, and is not answerable to the nature of things. The argument has several related incarnations in Wittgenstein’s post-Tractatus writings, and has given rise to a number of important insights, both critical and constructive. In this paper I will argue for a potential connection between Wittgenstein’s autonomy argument and some more recent internalist arguments for the autonomy of semantics. My main motivation for establishing this connection comes from the fact that the later Wittgenstein’s comments on grammar and meaning stand in opposition to some of the core assumptions of semantic externalism.

  20. Functional MRI approach for assessing hemispheric predominance of regions activated by a phonological and a semantic task

    Energy Technology Data Exchange (ETDEWEB)

    Cousin, Emilie; Peyrin, Carole; Pichat, Cedric [Laboratoire de Psychologie et Neurocognition, UMR CNRS 5105, Universite Pierre Mendes-France, BP 47, 38040 Grenoble Cedex 09 (France); Lamalle, Laurent; Le Bas, Jean-Francois [Unite IRM, IFR1, CHU Grenoble (France); Baciu, Monica [Laboratoire de Psychologie et Neurocognition, UMR CNRS 5105, Universite Pierre Mendes-France, BP 47, 38040 Grenoble Cedex 09 (France)], E-mail: mbaciu@upmf-grenoble.fr

    2007-08-15

    This fMRI study performed in healthy subjects aimed at using a statistical approach in order to determine significant functional differences between hemispheres and to assess specialized regions activated during a phonological and during a semantic task. This approach ('flip' method and subsequent statistical analyses of the parameter estimates extracted from regions of interest) allows identifying: (a) hemispheric specialized regions for each language task [semantic (living categorization) and phonological (rhyme detection)] and (b) condition-specific regions with respect to paradigm conditions (task and control). Our results showed that the rhyme-specific task regions were the inferior frontal (sub-region of BA 44, 45) and left inferior parietal (BA 40, 39) lobules. Furthermore, within the inferior parietal lobule, the angular gyrus was specific to target (rhyming) items (related to successfully grapho-phonemic processing). The categorization-specific task regions were the left inferior frontal (sub-region of BA 44, 45) and superior temporal (BA 22) cortices. Furthermore, the superior temporal gyrus was related to non-target (non-living) items (correlated to task difficulty). The relatively new approach used in this study has the advantage of providing: (a) statistical significance of the hemispheric specialized regions for a given language task and (b) supplementary information in terms of paradigm condition-specificity of the activated regions. The results (standard hemispheric specialized regions for a semantic and for a phonological task) obtained in healthy subjects may constitute a basement for mapping language and assessing hemispheric predominance in epileptic patients before surgery and avoiding post-surgical impairments of language.

  1. Functional MRI approach for assessing hemispheric predominance of regions activated by a phonological and a semantic task

    International Nuclear Information System (INIS)

    Cousin, Emilie; Peyrin, Carole; Pichat, Cedric; Lamalle, Laurent; Le Bas, Jean-Francois; Baciu, Monica

    2007-01-01

    This fMRI study performed in healthy subjects aimed at using a statistical approach in order to determine significant functional differences between hemispheres and to assess specialized regions activated during a phonological and during a semantic task. This approach ('flip' method and subsequent statistical analyses of the parameter estimates extracted from regions of interest) allows identifying: (a) hemispheric specialized regions for each language task [semantic (living categorization) and phonological (rhyme detection)] and (b) condition-specific regions with respect to paradigm conditions (task and control). Our results showed that the rhyme-specific task regions were the inferior frontal (sub-region of BA 44, 45) and left inferior parietal (BA 40, 39) lobules. Furthermore, within the inferior parietal lobule, the angular gyrus was specific to target (rhyming) items (related to successfully grapho-phonemic processing). The categorization-specific task regions were the left inferior frontal (sub-region of BA 44, 45) and superior temporal (BA 22) cortices. Furthermore, the superior temporal gyrus was related to non-target (non-living) items (correlated to task difficulty). The relatively new approach used in this study has the advantage of providing: (a) statistical significance of the hemispheric specialized regions for a given language task and (b) supplementary information in terms of paradigm condition-specificity of the activated regions. The results (standard hemispheric specialized regions for a semantic and for a phonological task) obtained in healthy subjects may constitute a basement for mapping language and assessing hemispheric predominance in epileptic patients before surgery and avoiding post-surgical impairments of language

  2. Wernicke's Aphasia Reflects a Combination of Acoustic-Phonological and Semantic Control Deficits: A Case-Series Comparison of Wernicke's Aphasia, Semantic Dementia and Semantic Aphasia

    Science.gov (United States)

    Robson, Holly; Sage, Karen; Lambon Ralph, Matthew A.

    2012-01-01

    Wernicke's aphasia (WA) is the classical neurological model of comprehension impairment and, as a result, the posterior temporal lobe is assumed to be critical to semantic cognition. This conclusion is potentially confused by (a) the existence of patient groups with semantic impairment following damage to other brain regions (semantic dementia and…

  3. Hierarchical Semantic Model of Geovideo

    Directory of Open Access Journals (Sweden)

    XIE Xiao

    2015-05-01

    Full Text Available The public security incidents were getting increasingly challenging with regard to their new features, including multi-scale mobility, multistage dynamic evolution, as well as spatiotemporal concurrency and uncertainty in the complex urban environment. However, the existing video models, which were used/designed for independent archive or local analysis of surveillance video, have seriously inhibited emergency response to the urgent requirements.Aiming at the explicit representation of change mechanism in video, the paper proposed a novel hierarchical geovideo semantic model using UML. This model was characterized by the hierarchical representation of both data structure and semantics based on the change-oriented three domains (feature domain, process domain and event domain instead of overall semantic description of video streaming; combining both geographical semantics and video content semantics, in support of global semantic association between multiple geovideo data. The public security incidents by video surveillance are inspected as an example to illustrate the validity of this model.

  4. Mapping the Structure of Semantic Memory

    Science.gov (United States)

    Morais, Ana Sofia; Olsson, Henrik; Schooler, Lael J.

    2013-01-01

    Aggregating snippets from the semantic memories of many individuals may not yield a good map of an individual's semantic memory. The authors analyze the structure of semantic networks that they sampled from individuals through a new snowball sampling paradigm during approximately 6 weeks of 1-hr daily sessions. The semantic networks of individuals…

  5. Semantic Reasoning for Scene Interpretation

    DEFF Research Database (Denmark)

    Jensen, Lars Baunegaard With; Baseski, Emre; Pugeault, Nicolas

    2008-01-01

    In this paper, we propose a hierarchical architecture for representing scenes, covering 2D and 3D aspects of visual scenes as well as the semantic relations between the different aspects. We argue that labeled graphs are a suitable representational framework for this representation and demonstrat...

  6. Causality in the semantics of Esterel : revisited

    NARCIS (Netherlands)

    Mousavi, M.R.; Klin, B.; Sobocinski, P.

    2010-01-01

    We re-examine the challenges concerning causality in the semantics of Esterel and show that they pertain to the known issues in the semantics of Structured Operational Semantics with negative premises. We show that the solutions offered for the semantics of SOS also provide answers to the semantic

  7. The effects of semantic congruency: a research of audiovisual P300-speller.

    Science.gov (United States)

    Cao, Yong; An, Xingwei; Ke, Yufeng; Jiang, Jin; Yang, Hanjun; Chen, Yuqian; Jiao, Xuejun; Qi, Hongzhi; Ming, Dong

    2017-07-25

    Over the past few decades, there have been many studies of aspects of brain-computer interface (BCI). Of particular interests are event-related potential (ERP)-based BCI spellers that aim at helping mental typewriting. Nowadays, audiovisual unimodal stimuli based BCI systems have attracted much attention from researchers, and most of the existing studies of audiovisual BCIs were based on semantic incongruent stimuli paradigm. However, no related studies had reported that whether there is difference of system performance or participant comfort between BCI based on semantic congruent paradigm and that based on semantic incongruent paradigm. The goal of this study was to investigate the effects of semantic congruency in system performance and participant comfort in audiovisual BCI. Two audiovisual paradigms (semantic congruent and incongruent) were adopted, and 11 healthy subjects participated in the experiment. High-density electrical mapping of ERPs and behavioral data were measured for the two stimuli paradigms. The behavioral data indicated no significant difference between congruent and incongruent paradigms for offline classification accuracy. Nevertheless, eight of the 11 participants reported their priority to semantic congruent experiment, two reported no difference between the two conditions, and only one preferred the semantic incongruent paradigm. Besides, the result indicted that higher amplitude of ERP was found in incongruent stimuli based paradigm. In a word, semantic congruent paradigm had a better participant comfort, and maintained the same recognition rate as incongruent paradigm. Furthermore, our study suggested that the paradigm design of spellers must take both system performance and user experience into consideration rather than merely pursuing a larger ERP response.

  8. Semantic Representatives of the Concept

    Directory of Open Access Journals (Sweden)

    Elena N. Tsay

    2013-01-01

    Full Text Available In the article concept as one of the principle notions of cognitive linguistics is investigated. Considering concept as culture phenomenon, having language realization and ethnocultural peculiarities, the description of the concept “happiness” is presented. Lexical and semantic paradigm of the concept of happiness correlates with a great number of lexical and semantic variants. In the work semantic representatives of the concept of happiness, covering supreme spiritual values are revealed and semantic interpretation of their functioning in the Biblical discourse is given.

  9. System semantics of explanatory dictionaries

    Directory of Open Access Journals (Sweden)

    Volodymyr Shyrokov

    2015-11-01

    Full Text Available System semantics of explanatory dictionaries Some semantic properties of the language to be followed from the structure of lexicographical systems of big explanatory dictionaries are considered. The hyperchains and hypercycles are determined as the definite kind of automorphisms of the lexicographical system of explanatory dictionary. Some semantic consequencies following from the principles of lexicographic closure and lexicographic completeness are investigated using the hyperchains and hypercycles formalism. The connection between the hypercyle properties of the lexicographical system semantics and Goedel’s incompleteness theorem is discussed.

  10. Language-Agnostic Relation Extraction from Abstracts in Wikis

    Directory of Open Access Journals (Sweden)

    Nicolas Heist

    2018-03-01

    Full Text Available Large-scale knowledge graphs, such as DBpedia, Wikidata, or YAGO, can be enhanced by relation extraction from text, using the data in the knowledge graph as training data, i.e., using distant supervision. While most existing approaches use language-specific methods (usually for English, we present a language-agnostic approach that exploits background knowledge from the graph instead of language-specific techniques and builds machine learning models only from language-independent features. We demonstrate the extraction of relations from Wikipedia abstracts, using the twelve largest language editions of Wikipedia. From those, we can extract 1.6 M new relations in DBpedia at a level of precision of 95%, using a RandomForest classifier trained only on language-independent features. We furthermore investigate the similarity of models for different languages and show an exemplary geographical breakdown of the information extracted. In a second series of experiments, we show how the approach can be transferred to DBkWik, a knowledge graph extracted from thousands of Wikis. We discuss the challenges and first results of extracting relations from a larger set of Wikis, using a less formalized knowledge graph.

  11. Grammatical markers switch roles and elicit different electrophysiological responses under shallow and deep semantic requirements.

    Science.gov (United States)

    Soshi, Takahiro; Nakajima, Heizo; Hagiwara, Hiroko

    2016-10-01

    Static knowledge about the grammar of a natural language is represented in the cortico-subcortical system. However, the differences in dynamic verbal processing under different cognitive conditions are unclear. To clarify this, we conducted an electrophysiological experiment involving a semantic priming paradigm in which semantically congruent or incongruent word sequences (prime nouns-target verbs) were randomly presented. We examined the event-related brain potentials that occurred in response to congruent and incongruent target words that were preceded by primes with or without grammatical case markers. The two participant groups performed either the shallow (lexical judgment) or deep (direct semantic judgment) semantic tasks. We hypothesized that, irrespective of the case markers, the congruent targets would reduce centro-posterior N400 activities under the deep semantic condition, which induces selective attention to the semantic relatedness of content words. However, the same congruent targets with correct case markers would reduce lateralized negativity under the shallow semantic condition because grammatical case markers are related to automatic structural integration under semantically unattended conditions. We observed that congruent targets (e.g., 'open') that were preceded by primes with congruent case markers (e.g., 'shutter-object case') reduced lateralized negativity under the shallow semantic condition. In contrast, congruent targets, irrespective of case markers, consistently yielded N400 reductions under the deep semantic condition. To summarize, human neural verbal processing differed in response to the same grammatical markers in the same verbal expressions under semantically attended or unattended conditions.

  12. On a syntactic-semantic model with the locative case

    Directory of Open Access Journals (Sweden)

    Antonić Ivana

    2008-01-01

    Full Text Available The topic of this paper is a syntactic-semantic model whose distinctive element is the locative case with the preposition U (IN and the relevant feature (+ human being. This model is realized in three different variants - with the intransitive (A or transitive verb (B, where the nominative in the function of subject and the locative indicate different (B1 or the same (B2 referents. Furthermore, the verb belongs to a semantic class which denotes emerging, stimulation, duration, fading away, diminishing or change in the intensity, in principle, of any phenomenon, and concretely in this model such verbs appear in the collocational link with the nouns implying man's psychological, physiological or mental states, feelings or mood. With an adequate analytic procedure, all the three variants of this model are approached from the syntactic-semantic and pragmatic perspective. The paper points to the causative semantics of these structures, reduced to the metalinguistic formula 'make that X V', which confirms that the semantics of these verb-noun collocational links, syntactically speaking, condenses a complex two-member sentential structure represented by the semantically deficient verb (= causative component in the basic, matrix structure, and the complement clause with the conjunction DA (THAT and the basic verb. And precisely from this semantic feature there follows that the notion in the locative case semantically, actually, represents the BEARER of a physiological, physiological or mental state, feeling, mood, so that it represents the GRAMMATICAL SUBJECT of the corresponding basic subordinated predication whose exponent, actually, is the grammatical subject in the structure with the intransitive verb (or with the syntactically-semantically intransitive verb structure, that is the object in the structure with the transitive verb. Two possible semantic interpretations of this model are presented: the one related to the referential pointing to the

  13. Semantic Meaning in Attitudinal Lexemes in the Domain of Kesenangan (Joy in Indonesian: An Analysis of Meaning Components and Lexical Relation

    Directory of Open Access Journals (Sweden)

    Prima Gusti Yanti

    2017-04-01

    Full Text Available The attitudinal lexeme on the domain of kesenangan in Indonesia language has not shown such clear meaning relationship, for both the common and diagnostic meaning of the lexemes. Those lexemes have such circular definitions, confusing upon their use. This study is conducted using a qualitative research approach employing content analysis technique. The aim of this study is to find out lexical relation and semantic meaning in attitudinal lexeme in the domain of kesenangan (joy in Indonesian language. Data is collected from seven Indonesian dictionaries, two magazines, five newspapers, and six literary works. All data is analyzed using a component analysis in the semantic theory. The research findings show that fourteen (14 lexemes (senang, nikmat, enak, puas, asyik, sukacita, ria, bangga, lega, bahagia, gembira, girang, riang, and ceria of attitudinal lexemes are related with the domain of kesenangan. The result shows that hyponymy and synonymy lexical relations occur in the domain of kesenangan. Synonymy relation consists of near-synonymy and propositional synonymy. In this case, absolute synonymy is not found.

  14. Effect of hearing loss on semantic access by auditory and audiovisual speech in children.

    Science.gov (United States)

    Jerger, Susan; Tye-Murray, Nancy; Damian, Markus F; Abdi, Hervé

    2013-01-01

    This research studied whether the mode of input (auditory versus audiovisual) influenced semantic access by speech in children with sensorineural hearing impairment (HI). Participants, 31 children with HI and 62 children with normal hearing (NH), were tested with the authors' new multimodal picture word task. Children were instructed to name pictures displayed on a monitor and ignore auditory or audiovisual speech distractors. The semantic content of the distractors was varied to be related versus unrelated to the pictures (e.g., picture distractor of dog-bear versus dog-cheese, respectively). In children with NH, picture-naming times were slower in the presence of semantically related distractors. This slowing, called semantic interference, is attributed to the meaning-related picture-distractor entries competing for selection and control of the response (the lexical selection by competition hypothesis). Recently, a modification of the lexical selection by competition hypothesis, called the competition threshold (CT) hypothesis, proposed that (1) the competition between the picture-distractor entries is determined by a threshold, and (2) distractors with experimentally reduced fidelity cannot reach the CT. Thus, semantically related distractors with reduced fidelity do not produce the normal interference effect, but instead no effect or semantic facilitation (faster picture naming times for semantically related versus unrelated distractors). Facilitation occurs because the activation level of the semantically related distractor with reduced fidelity (1) is not sufficient to exceed the CT and produce interference but (2) is sufficient to activate its concept, which then strengthens the activation of the picture and facilitates naming. This research investigated whether the proposals of the CT hypothesis generalize to the auditory domain, to the natural degradation of speech due to HI, and to participants who are children. Our multimodal picture word task allowed us

  15. Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services

    Science.gov (United States)

    Daniel, Christel; Ouagne, David; Sadou, Eric; Forsberg, Kerstin; Gilchrist, Mark Mc; Zapletal, Eric; Paris, Nicolas; Hussain, Sajjad; Jaulent, Marie-Christine; MD, Dipka Kalra

    2016-01-01

    With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data. PMID:27570649

  16. Long-term interference at the semantic level: Evidence from blocked-cyclic picture matching.

    Science.gov (United States)

    Wei, Tao; Schnur, Tatiana T

    2016-01-01

    Processing semantically related stimuli creates interference across various domains of cognition, including language and memory. In this study, we identify the locus and mechanism of interference when retrieving meanings associated with words and pictures. Subjects matched a probe stimulus (e.g., cat) to its associated target picture (e.g., yarn) from an array of unrelated pictures. Across trials, probes were either semantically related or unrelated. To test the locus of interference, we presented probes as either words or pictures. If semantic interference occurs at the stage common to both tasks, that is, access to semantic representations, then interference should occur in both probe presentation modalities. Results showed clear semantic interference effects independent of presentation modality and lexical frequency, confirming a semantic locus of interference in comprehension. To test the mechanism of interference, we repeated trials across 4 presentation cycles and manipulated the number of unrelated intervening trials (zero vs. two). We found that semantic interference was additive across cycles and survived 2 intervening trials, demonstrating interference to be long-lasting as opposed to short-lived. However, interference was smaller with zero versus 2 intervening trials, which we interpret to suggest that short-lived facilitation counteracted the long-lived interference. We propose that retrieving meanings associated with words/pictures from the same semantic category yields both interference due to long-lasting changes in connection strength between semantic representations (i.e., incremental learning) and facilitation caused by short-lived residual activation. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  17. The Semantic Web Revisited

    OpenAIRE

    Shadbolt, Nigel; Berners-Lee, Tim; Hall, Wendy

    2006-01-01

    The original Scientific American article on the Semantic Web appeared in 2001. It described the evolution of a Web that consisted largely of documents for humans to read to one that included data and information for computers to manipulate. The Semantic Web is a Web of actionable information--information derived from data through a semantic theory for interpreting the symbols.This simple idea, however, remains largely unrealized. Shopbots and auction bots abound on the Web, but these are esse...

  18. Semantic Search of Web Services

    Science.gov (United States)

    Hao, Ke

    2013-01-01

    This dissertation addresses semantic search of Web services using natural language processing. We first survey various existing approaches, focusing on the fact that the expensive costs of current semantic annotation frameworks result in limited use of semantic search for large scale applications. We then propose a vector space model based service…

  19. Conceptual Model Formalization in a Semantic Interoperability Service Framework: Transforming Relational Database Schemas to OWL.

    Science.gov (United States)

    Bravo, Carlos; Suarez, Carlos; González, Carolina; López, Diego; Blobel, Bernd

    2014-01-01

    Healthcare information is distributed through multiple heterogeneous and autonomous systems. Access to, and sharing of, distributed information sources are a challenging task. To contribute to meeting this challenge, this paper presents a formal, complete and semi-automatic transformation service from Relational Databases to Web Ontology Language. The proposed service makes use of an algorithm that allows to transform several data models of different domains by deploying mainly inheritance rules. The paper emphasizes the relevance of integrating the proposed approach into an ontology-based interoperability service to achieve semantic interoperability.

  20. Is semantic verbal fluency impairment explained by executive function deficits in schizophrenia?

    Directory of Open Access Journals (Sweden)

    Arthur A. Berberian

    2016-01-01

    Full Text Available Objective: To investigate if verbal fluency impairment in schizophrenia reflects executive function deficits or results from degraded semantic store or inefficient search and retrieval strategies. Method: Two groups were compared: 141 individuals with schizophrenia and 119 healthy age and education-matched controls. Both groups performed semantic and phonetic verbal fluency tasks. Performance was evaluated using three scores, based on 1 number of words generated; 2 number of clustered/related words; and 3 switching score. A fourth performance score based on the number of clusters was also measured. Results: SZ individuals produced fewer words than controls. After controlling for the total number of words produced, a difference was observed between the groups in the number of cluster-related words generated in the semantic task. In both groups, the number of words generated in the semantic task was higher than that generated in the phonemic task, although a significant group vs. fluency type interaction showed that subjects with schizophrenia had disproportionate semantic fluency impairment. Working memory was positively associated with increased production of words within clusters and inversely correlated with switching. Conclusion: Semantic fluency impairment may be attributed to an inability (resulting from reduced cognitive control to distinguish target signal from competing noise and to maintain cues for production of memory probes.

  1. Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

    Science.gov (United States)

    Fox, P.

    2012-04-01

    The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

  2. The absoluteness of semantic processing: lessons from the analysis of temporal clusters in phonemic verbal fluency.

    Directory of Open Access Journals (Sweden)

    Isabelle Vonberg

    Full Text Available For word production, we may consciously pursue semantic or phonological search strategies, but it is uncertain whether we can retrieve the different aspects of lexical information independently from each other. We therefore studied the spread of semantic information into words produced under exclusively phonemic task demands.42 subjects participated in a letter verbal fluency task, demanding the production of as many s-words as possible in two minutes. Based on curve fittings for the time courses of word production, output spurts (temporal clusters considered to reflect rapid lexical retrieval based on automatic activation spread, were identified. Semantic and phonemic word relatedness within versus between these clusters was assessed by respective scores (0 meaning no relation, 4 maximum relation.Subjects produced 27.5 (±9.4 words belonging to 6.7 (±2.4 clusters. Both phonemically and semantically words were more related within clusters than between clusters (phon: 0.33±0.22 vs. 0.19±0.17, p<.01; sem: 0.65±0.29 vs. 0.37±0.29, p<.01. Whereas the extent of phonemic relatedness correlated with high task performance, the contrary was the case for the extent of semantic relatedness.The results indicate that semantic information spread occurs, even if the consciously pursued word search strategy is purely phonological. This, together with the negative correlation between semantic relatedness and verbal output suits the idea of a semantic default mode of lexical search, acting against rapid task performance in the given scenario of phonemic verbal fluency. The simultaneity of enhanced semantic and phonemic word relatedness within the same temporal cluster boundaries suggests an interaction between content and sound-related information whenever a new semantic field has been opened.

  3. Behavioural and magnetoencephalographic evidence for the interaction between semantic and episodic memory in healthy elderly subjects.

    Science.gov (United States)

    La Corte, Valentina; Dalla Barba, Gianfranco; Lemaréchal, Jean-Didier; Garnero, Line; George, Nathalie

    2012-10-01

    The relationship between episodic and semantic memory systems has long been debated. Some authors argue that episodic memory is contingent on semantic memory (Tulving 1984), while others postulate that both systems are independent since they can be selectively damaged (Squire 1987). The interaction between these memory systems is particularly important in the elderly, since the dissociation of episodic and semantic memory defects characterize different aging-related pathologies. Here, we investigated the interaction between semantic knowledge and episodic memory processes associated with faces in elderly subjects using an experimental paradigm where the semantic encoding of famous and unknown faces was compared to their episodic recognition. Results showed that the level of semantic awareness of items affected the recognition of those items in the episodic memory task. Event-related magnetic fields confirmed this interaction between episodic and semantic memory: ERFs related to the old/new effect during the episodic task were markedly different for famous and unknown faces. The old/new effect for famous faces involved sustained activities maximal over right temporal sensors, showing a spatio-temporal pattern partly similar to that found for famous versus unknown faces during the semantic task. By contrast, an old/new effect for unknown faces was observed on left parieto-occipital sensors. These findings suggest that the episodic memory for famous faces activated the retrieval of stored semantic information, whereas it was based on items' perceptual features for unknown faces. Overall, our results show that semantic information interfered markedly with episodic memory processes and suggested that the neural substrates of these two memory systems overlap.

  4. LAIR: A Language for Automated Semantics-Aware Text Sanitization based on Frame Semantics

    DEFF Research Database (Denmark)

    Hedegaard, Steffen; Houen, Søren; Simonsen, Jakob Grue

    2009-01-01

    We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires on...... with automated redaction of web pages for subjectively undesirable content; initial experiments suggest that using a small language based on semantic recognition of undesirable terms can be highly useful as a supplement to traditional methods of text sanitization.......We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires only...... limited prior programming experience. It neither contain scripting or I/O primitives, nor does it contain general loop constructions and is not Turing-complete. We have implemented a \\lair{} compiler and integrated it in a pipeline for automated redaction of web pages. We detail our experience...

  5. Semantic dementia without surface dyslexia in Spanish: unimpaired reading with impaired semantics.

    Science.gov (United States)

    Wilson, Maximiliano A; Martínez-Cuitiño, Macarena

    2012-01-01

    Surface dyslexia has been attributed to an overreliance on the sub-lexical route for reading. Typically, surface dyslexic patients commit regularisation errors when reading irregular words. Also, semantic dementia has often been associated with surface dyslexia, leading to some explanations of the reading impairment that stress the role of semantics in irregular word reading. Nevertheless, some patients have been reported with unimpaired ability to read irregular words, even though they show severe comprehension impairment. We present the case of M.B., the first Spanish-speaking semantic dementia patient to be reported who shows unimpaired reading of non-words, regular words, and - most strikingly - irregular loan words. M.B. has severely impaired comprehension of the same words he reads correctly (whether regular or irregular). We argue that M.B.'s pattern of performance shows that irregular words can be correctly read even with impaired semantic knowledge corresponding to those words.

  6. Comparing Refinements for Failure and Bisimulation Semantics

    NARCIS (Netherlands)

    Eshuis, H.; Fokkinga, M.M.

    2002-01-01

    Refinement in bisimulation semantics is defined differently from refinement in failure semantics: in bisimulation semantics refinement is based on simulations between labelled transition systems, whereas in failure semantics refinement is based on inclusions between failure systems. There exist

  7. Grammatical markers switch roles and elicit different electrophysiological responses under shallow and deep semantic requirements

    Directory of Open Access Journals (Sweden)

    Takahiro Soshi

    2016-10-01

    Full Text Available Static knowledge about the grammar of a natural language is represented in the cortico-subcortical system. However, the differences in dynamic verbal processing under different cognitive conditions are unclear. To clarify this, we conducted an electrophysiological experiment involving a semantic priming paradigm in which semantically congruent or incongruent word sequences (prime nouns–target verbs were randomly presented. We examined the event-related brain potentials that occurred in response to congruent and incongruent target words that were preceded by primes with or without grammatical case markers. The two participant groups performed either the shallow (lexical judgment or deep (direct semantic judgment semantic tasks. We hypothesized that, irrespective of the case markers, the congruent targets would reduce centro-posterior N400 activities under the deep semantic condition, which induces selective attention to the semantic relatedness of content words. However, the same congruent targets with correct case markers would reduce lateralized negativity under the shallow semantic condition because grammatical case markers are related to automatic structural integration under semantically unattended conditions. We observed that congruent targets (e.g., ‘open' that were preceded by primes with congruent case markers (e.g., ‘shutter-object case' reduced lateralized negativity under the shallow semantic condition. In contrast, congruent targets, irrespective of case markers, consistently yielded N400 reductions under the deep semantic condition. To summarize, human neural verbal processing differed in response to the same grammatical markers in the same verbal expressions under semantically attended or unattended conditions. Keyword: Neuroscience

  8. Using semantic memory to boost 'episodic' recall in a case of developmental amnesia.

    Science.gov (United States)

    Brandt, Karen R; Gardiner, John M; Vargha-Khadem, Faraneh; Baddeley, Alan D; Mishkin, Mortimer

    2006-07-17

    We report two experiments that investigated factors that might boost 'episodic' recall for Jon, a developmental amnesic whose episodic memory is gravely impaired but whose semantic memory seems relatively normal. Experiment 1 showed that Jon's recall improved following a semantic study task compared with a non-semantic study task, as well as following four repeated study trials compared with only one. Experiment 2 additionally revealed that Jon's recall improved after acting compared with reading action phrases at study, but only if the phrases were well integrated semantically. The results provide some support for the hypothesis that Jon's 'episodic' recall depends on the extent to which he is able to retrieve events using semantic memory.

  9. Semantics-based Automated Web Testing

    Directory of Open Access Journals (Sweden)

    Hai-Feng Guo

    2015-08-01

    Full Text Available We present TAO, a software testing tool performing automated test and oracle generation based on a semantic approach. TAO entangles grammar-based test generation with automated semantics evaluation using a denotational semantics framework. We show how TAO can be incorporated with the Selenium automation tool for automated web testing, and how TAO can be further extended to support automated delta debugging, where a failing web test script can be systematically reduced based on grammar-directed strategies. A real-life parking website is adopted throughout the paper to demonstrate the effectivity of our semantics-based web testing approach.

  10. Benchmarking semantic web technology

    CERN Document Server

    García-Castro, R

    2009-01-01

    This book addresses the problem of benchmarking Semantic Web Technologies; first, from a methodological point of view, proposing a general methodology to follow in benchmarking activities over Semantic Web Technologies and, second, from a practical point of view, presenting two international benchmarking activities that involved benchmarking the interoperability of Semantic Web technologies using RDF(S) as the interchange language in one activity and OWL in the other.The book presents in detail how the different resources needed for these interoperability benchmarking activities were defined:

  11. Using Semantic Association to Extend and Infer Literature-Oriented Relativity Between Terms.

    Science.gov (United States)

    Cheng, Liang; Li, Jie; Hu, Yang; Jiang, Yue; Liu, Yongzhuang; Chu, Yanshuo; Wang, Zhenxing; Wang, Yadong

    2015-01-01

    Relative terms often appear together in the literature. Methods have been presented for weighting relativity of pairwise terms by their co-occurring literature and inferring new relationship. Terms in the literature are also in the directed acyclic graph of ontologies, such as Gene Ontology and Disease Ontology. Therefore, semantic association between terms may help for establishing relativities between terms in literature. However, current methods do not use these associations. In this paper, an adjusted R-scaled score (ARSS) based on information content (ARSSIC) method is introduced to infer new relationship between terms. First, set inclusion relationship between terms of ontology was exploited to extend relationships between these terms and literature. Next, the ARSS method was presented to measure relativity between terms across ontologies according to these extensional relationships. Then, the ARSSIC method using ratios of information shared of term's ancestors was designed to infer new relationship between terms across ontologies. The result of the experiment shows that ARSS identified more pairs of statistically significant terms based on corresponding gene sets than other methods. And the high average area under the receiver operating characteristic curve (0.9293) shows that ARSSIC achieved a high true positive rate and a low false positive rate. Data is available at http://mlg.hit.edu.cn/ARSSIC/.

  12. Semantic Web and Contextual Information: Semantic Network Analysis of Online Journalistic Texts

    Science.gov (United States)

    Lim, Yon Soo

    This study examines why contextual information is important to actualize the idea of semantic web, based on a case study of a socio-political issue in South Korea. For this study, semantic network analyses were conducted regarding English-language based 62 blog posts and 101 news stories on the web. The results indicated the differences of the meaning structures between blog posts and professional journalism as well as between conservative journalism and progressive journalism. From the results, this study ascertains empirical validity of current concerns about the practical application of the new web technology, and discusses how the semantic web should be developed.

  13. The impact of auditory white noise on semantic priming.

    Science.gov (United States)

    Angwin, Anthony J; Wilson, Wayne J; Copland, David A; Barry, Robert J; Myatt, Grace; Arnott, Wendy L

    2018-04-10

    It has been proposed that white noise can improve cognitive performance for some individuals, particularly those with lower attention, and that this effect may be mediated by dopaminergic circuitry. Given existing evidence that semantic priming is modulated by dopamine, this study investigated whether white noise can facilitate semantic priming. Seventy-eight adults completed an auditory semantic priming task with and without white noise, at either a short or long inter-stimulus interval (ISI). Measures of both direct and indirect semantic priming were examined. Analysis of the results revealed significant direct and indirect priming effects at each ISI in noise and silence, however noise significantly reduced the magnitude of indirect priming. Analyses of subgroups with higher versus lower attention revealed a reduction to indirect priming in noise relative to silence for participants with lower executive and orienting attention. These findings suggest that white noise focuses automatic spreading activation, which may be driven by modulation of dopaminergic circuitry. Copyright © 2018 Elsevier Inc. All rights reserved.

  14. Different Loci of Semantic Interference in Picture Naming vs. Word-Picture Matching Tasks.

    Science.gov (United States)

    Harvey, Denise Y; Schnur, Tatiana T

    2016-01-01

    Naming pictures and matching words to pictures belonging to the same semantic category impairs performance relative to when stimuli come from different semantic categories (i.e., semantic interference). Despite similar semantic interference phenomena in both picture naming and word-picture matching tasks, the locus of interference has been attributed to different levels of the language system - lexical in naming and semantic in word-picture matching. Although both tasks involve access to shared semantic representations, the extent to which interference originates and/or has its locus at a shared level remains unclear, as these effects are often investigated in isolation. We manipulated semantic context in cyclical picture naming and word-picture matching tasks, and tested whether factors tapping semantic-level (generalization of interference to novel category items) and lexical-level processes (interactions with lexical frequency) affected the magnitude of interference, while also assessing whether interference occurs at a shared processing level(s) (transfer of interference across tasks). We found that semantic interference in naming was sensitive to both semantic- and lexical-level processes (i.e., larger interference for novel vs. old and low- vs. high-frequency stimuli), consistent with a semantically mediated lexical locus. Interference in word-picture matching exhibited stable interference for old and novel stimuli and did not interact with lexical frequency. Further, interference transferred from word-picture matching to naming. Together, these experiments provide evidence to suggest that semantic interference in both tasks originates at a shared processing stage (presumably at the semantic level), but that it exerts its effect at different loci when naming pictures vs. matching words to pictures.

  15. Semantic web for the working ontologist effective modeling in RDFS and OWL

    CERN Document Server

    Allemang, Dean

    2011-01-01

    Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications. Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on

  16. A Postcolonial Semantics of Personhood

    DEFF Research Database (Denmark)

    Levisen, Carsten

    that provide an answer to the question: “what makes up a person?” The paper aims toarticulate semantic explications and cultural scripts for personhood constructs in Bislama, beingmindful of the anglicizations, contradictions, and reinventions that are characteristic of postcolonialdiscourse......, 2013-2015 (Levisen 2016a, 2016b). I willfocus on the keyword tingting ‘mind, heart’ (from English ‘think-think’), and the related concepts speret(from English ‘spirit’), devil (from English ‘devil’), and pija (from English ‘picture’), as well as morerecent imports from English: maen (mind), sol (soul...... levels. Traditionalterms like devil and pija are being problematized by urban speakers, and are both in decline. Sol,maen, and had have become more common, and speret/spirit has undergone a semanticanglicization. Tingting remains the key construct, around which Bislama personhood semantics isorganized...

  17. Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

    DEFF Research Database (Denmark)

    Danvy, Olivier

    2009-01-01

    We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fus...

  18. A Denotational Semantics for Logic Programming

    DEFF Research Database (Denmark)

    Frandsen, Gudmund Skovbjerg

    A fully abstract denotational semantics for logic programming has not been constructed yet. In this paper we present a denotational semantics that is almost fully abstract. We take the meaning of a logic program to be an element in a Plotkin power domain of substitutions. In this way our result...... shows that standard domain constructions suffice, when giving a semantics for logic programming. Using the well-known fixpoint semantics of logic programming we have to consider two different fixpoints in order to obtain information about both successful and failed computations. In contrast, our...... semantics is uniform in that the (single) meaning of a logic program contains information about both successful, failed and infinite computations. Finally, based on the full abstractness result, we argue that the detail level of substitutions is needed in any denotational semantics for logic programming....

  19. CASL The Common Algebraic Specification Language Semantics

    DEFF Research Database (Denmark)

    Haxthausen, Anne

    1998-01-01

    This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the first complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop at Cachan in November 1998.......This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the first complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop at Cachan in November 1998....

  20. THE MALT EXTRACT, RELATIVE EXTRACT AND DIASTATIC POWER AS A VARIETAL CHARACTERISTIC OF MALTING BARLEY

    Directory of Open Access Journals (Sweden)

    Štefan Dráb

    2014-02-01

    Full Text Available Malting quality of barley depends on genetic and agro-ekological factors. Chemical composition of malting barley and its technological parameters are very important for malting and brewing, due to this fact the quality of barley must be strictly evaluated. The aim of this work was to evaluate the influence of variety, locality and year of production on the 5 technological parameters of malt: extract, relative extract at 45 °C, Kolbach index, diastatic power and friability. It was found out that the barley variety significantly influenced the following parameters: extract, relative extract and diastatic power. The growing locality weakly influenced qualitative parameters i.e. Kolbach index and relative extract at 45°C. The study confirmed the most significant impact of the year on the Kolbach index and friability.

  1. Determining the semantic similarities among Gene Ontology terms.

    Science.gov (United States)

    Taha, Kamal

    2013-05-01

    We present in this paper novel techniques that determine the semantic relationships among GeneOntology (GO) terms. We implemented these techniques in a prototype system called GoSE, which resides between user application and GO database. Given a set S of GO terms, GoSE would return another set S' of GO terms, where each term in S' is semantically related to each term in S. Most current research is focused on determining the semantic similarities among GO ontology terms based solely on their IDs and proximity to one another in the GO graph structure, while overlooking the contexts of the terms, which may lead to erroneous results. The context of a GO term T is the set of other terms, whose existence in the GO graph structure is dependent on T. We propose novel techniques that determine the contexts of terms based on the concept of existence dependency. We present a stack-based sort-merge algorithm employing these techniques for determining the semantic similarities among GO terms.We evaluated GoSE experimentally and compared it with three existing methods. The results of measuring the semantic similarities among genes in KEGG and Pfam pathways retrieved from the DBGET and Sanger Pfam databases, respectively, have shown that our method outperforms the other three methods in recall and precision.

  2. Functional neuroimaging of semantic and episodic musical memory.

    Science.gov (United States)

    Platel, Hervé

    2005-12-01

    The distinction between episodic and semantic memory has become very popular since it was first proposed by Tulving in 1972. So far, very few neuropsychological, psychophysical, and imaging studies have related to the mnemonic aspects of music, notably on the long-term memory features, and practically nothing is known about the functional anatomy of long-term memory for music. Numerous functional imaging studies have shown that retrieval from semantic and episodic memory is subserved by distinct neural networks. For instance, the HERA model (hemispheric encoding/retrieval asymmetry) ascribes to the left prefrontal cortex a preferential role in the encoding process of episodic material and the recall of semantic information, while the right prefrontal cortex would preferentially operate in the recall of episodic information. However, these results were essentially obtained with verbal and visuo-spatial material. We have done a study to determine the neural substrates underlying the semantic and episodic components of music using familiar and nonfamiliar melodic tunes. Two distinct patterns of activations were found: bilateral activation of the middle and superior frontal areas and precuneus for episodic memory, and activation of the medial and orbital frontal cortex bilaterally, left angular gyrus, and the anterior part of the left middle and superior temporal gyri for semantic memory. We discuss these findings in light of the available neuropsychological data obtained in brain-damaged subjects and functional neuroimaging studies.

  3. Bladder cancer treatment response assessment with radiomic, clinical, and radiologist semantic features

    Science.gov (United States)

    Gordon, Marshall N.; Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.; Paramagul, Chintana; Alva, Ajjai; Weizer, Alon Z.

    2018-02-01

    We are developing a decision support system for assisting clinicians in assessment of response to neoadjuvant chemotherapy for bladder cancer. Accurate treatment response assessment is crucial for identifying responders and improving quality of life for non-responders. An objective machine learning decision support system may help reduce variability and inaccuracy in treatment response assessment. We developed a predictive model to assess the likelihood that a patient will respond based on image and clinical features. With IRB approval, we retrospectively collected a data set of pre- and post- treatment CT scans along with clinical information from surgical pathology from 98 patients. A linear discriminant analysis (LDA) classifier was used to predict the likelihood that a patient would respond to treatment based on radiomic features extracted from CT urography (CTU), a radiologist's semantic feature, and a clinical feature extracted from surgical and pathology reports. The classification accuracy was evaluated using the area under the ROC curve (AUC) with a leave-one-case-out cross validation. The classification accuracy was compared for the systems based on radiomic features, clinical feature, and radiologist's semantic feature. For the system based on only radiomic features the AUC was 0.75. With the addition of clinical information from examination under anesthesia (EUA) the AUC was improved to 0.78. Our study demonstrated the potential of designing a decision support system to assist in treatment response assessment. The combination of clinical features, radiologist semantic features and CTU radiomic features improved the performance of the classifier and the accuracy of treatment response assessment.

  4. Semantic Web status model

    CSIR Research Space (South Africa)

    Gerber, AJ

    2006-06-01

    Full Text Available Semantic Web application areas are experiencing intensified interest due to the rapid growth in the use of the Web, together with the innovation and renovation of information content technologies. The Semantic Web is regarded as an integrator across...

  5. Connecting long distance: semantic distance in analogical reasoning modulates frontopolar cortex activity.

    Science.gov (United States)

    Green, Adam E; Kraemer, David J M; Fugelsang, Jonathan A; Gray, Jeremy R; Dunbar, Kevin N

    2010-01-01

    Solving problems often requires seeing new connections between concepts or events that seemed unrelated at first. Innovative solutions of this kind depend on analogical reasoning, a relational reasoning process that involves mapping similarities between concepts. Brain-based evidence has implicated the frontal pole of the brain as important for analogical mapping. Separately, cognitive research has identified semantic distance as a key characteristic of the kind of analogical mapping that can support innovation (i.e., identifying similarities across greater semantic distance reveals connections that support more innovative solutions and models). However, the neural substrates of semantically distant analogical mapping are not well understood. Here, we used functional magnetic resonance imaging (fMRI) to measure brain activity during an analogical reasoning task, in which we parametrically varied the semantic distance between the items in the analogies. Semantic distance was derived quantitatively from latent semantic analysis. Across 23 participants, activity in an a priori region of interest (ROI) in left frontopolar cortex covaried parametrically with increasing semantic distance, even after removing effects of task difficulty. This ROI was centered on a functional peak that we previously associated with analogical mapping. To our knowledge, these data represent a first empirical characterization of how the brain mediates semantically distant analogical mapping.

  6. Fuzzy Emotional Semantic Analysis and Automated Annotation of Scene Images

    Directory of Open Access Journals (Sweden)

    Jianfang Cao

    2015-01-01

    Full Text Available With the advances in electronic and imaging techniques, the production of digital images has rapidly increased, and the extraction and automated annotation of emotional semantics implied by images have become issues that must be urgently addressed. To better simulate human subjectivity and ambiguity for understanding scene images, the current study proposes an emotional semantic annotation method for scene images based on fuzzy set theory. A fuzzy membership degree was calculated to describe the emotional degree of a scene image and was implemented using the Adaboost algorithm and a back-propagation (BP neural network. The automated annotation method was trained and tested using scene images from the SUN Database. The annotation results were then compared with those based on artificial annotation. Our method showed an annotation accuracy rate of 91.2% for basic emotional values and 82.4% after extended emotional values were added, which correspond to increases of 5.5% and 8.9%, respectively, compared with the results from using a single BP neural network algorithm. Furthermore, the retrieval accuracy rate based on our method reached approximately 89%. This study attempts to lay a solid foundation for the automated emotional semantic annotation of more types of images and therefore is of practical significance.

  7. Hierarchy-associated semantic-rule inference framework for classifying indoor scenes

    Science.gov (United States)

    Yu, Dan; Liu, Peng; Ye, Zhipeng; Tang, Xianglong; Zhao, Wei

    2016-03-01

    Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

  8. When emotional prosody and semantics dance cheek to cheek: ERP evidence.

    Science.gov (United States)

    Kotz, Sonja A; Paulmann, Silke

    2007-06-02

    To communicate emotionally entails that a listener understands a verbal message but also the emotional prosody going along with it. So far the time course and interaction of these emotional 'channels' is still poorly understood. The current set of event-related brain potential (ERP) experiments investigated both the interactive time course of emotional prosody with semantics and of emotional prosody independent of emotional semantics using a cross-splicing method. In a probe verification task (Experiment 1) prosodic expectancy violations elicited a positivity, while a combined prosodic-semantic expectancy violation elicited a negativity. Comparable ERP results were obtained in an emotional prosodic categorization task (Experiment 2). The present data support different ERP responses with distinct time courses and topographies elicited as a function of prosodic expectancy and combined prosodic-semantic expectancy during emotional prosodic processing and combined emotional prosody/emotional semantic processing. These differences suggest that the interaction of more than one emotional channel facilitates subtle transitions in an emotional sentence context.

  9. Semantic Memory in the Clinical Progression of Alzheimer Disease.

    Science.gov (United States)

    Tchakoute, Christophe T; Sainani, Kristin L; Henderson, Victor W

    2017-09-01

    Semantic memory measures may be useful in tracking and predicting progression of Alzheimer disease. We investigated relationships among semantic memory tasks and their 1-year predictive value in women with Alzheimer disease. We conducted secondary analyses of a randomized clinical trial of raloxifene in 42 women with late-onset mild-to-moderate Alzheimer disease. We assessed semantic memory with tests of oral confrontation naming, category fluency, semantic recognition and semantic naming, and semantic density in written narrative discourse. We measured global cognition (Alzheimer Disease Assessment Scale, cognitive subscale), dementia severity (Clinical Dementia Rating sum of boxes), and daily function (Activities of Daily Living Inventory) at baseline and 1 year. At baseline and 1 year, most semantic memory scores correlated highly or moderately with each other and with global cognition, dementia severity, and daily function. Semantic memory task performance at 1 year had worsened one-third to one-half standard deviation. Factor analysis of baseline test scores distinguished processes in semantic and lexical retrieval (semantic recognition, semantic naming, confrontation naming) from processes in lexical search (semantic density, category fluency). The semantic-lexical retrieval factor predicted global cognition at 1 year. Considered separately, baseline confrontation naming and category fluency predicted dementia severity, while semantic recognition and a composite of semantic recognition and semantic naming predicted global cognition. No individual semantic memory test predicted daily function. Semantic-lexical retrieval and lexical search may represent distinct aspects of semantic memory. Semantic memory processes are sensitive to cognitive decline and dementia severity in Alzheimer disease.

  10. A Denotational Semantics for Communicating Unstructured Code

    Directory of Open Access Journals (Sweden)

    Nils Jähnig

    2015-03-01

    Full Text Available An important property of programming language semantics is that they should be compositional. However, unstructured low-level code contains goto-like commands making it hard to define a semantics that is compositional. In this paper, we follow the ideas of Saabas and Uustalu to structure low-level code. This gives us the possibility to define a compositional denotational semantics based on least fixed points to allow for the use of inductive verification methods. We capture the semantics of communication using finite traces similar to the denotations of CSP. In addition, we examine properties of this semantics and give an example that demonstrates reasoning about communication and jumps. With this semantics, we lay the foundations for a proof calculus that captures both, the semantics of unstructured low-level code and communication.

  11. A Semantics for Distributed Execution of Statemate

    DEFF Research Database (Denmark)

    Fränzle, Martin; Niehaus, Jürgen; Metzner, Alexander

    2003-01-01

    We present a semantics for the statechart variant implemented in the Statemate product of i-Logix. Our semantics enables distributed code generation for Statemate models in the context of rapid prototyping for embedded control applications. We argue that it seems impossible to efficiently generate......, the changes made regarding the interaction of distributed model parts are similar to the interaction between the model and its environment in the original semantics, thus giving designers a familiar execution model. The semantics has been implemented in Grace, a framework for rapid prototyping code generation...... distributed code using the original Statemate semantics. The new, distributed semantics has the advantages that, first, it enables the generation of efficient distributed code, second, it preserves many aspects of the original semantics for those parts of a model that are not distributed, and third...

  12. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Science.gov (United States)

    Walls, Ramona L; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

  13. Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies

    Science.gov (United States)

    Baskauf, Steve; Blum, Stanley; Bowers, Shawn; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Tuama, Éamonn Ó.; Schildhauer, Mark; Smith, Barry; Stucky, Brian J.; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers

  14. Semantic priming effects of synonyms, antonyms, frame, implication and verb-object categories

    Directory of Open Access Journals (Sweden)

    Elsa Skënderi-Rakipllari

    2017-12-01

    Full Text Available Semantic priming has been a major subject of interest for psycholinguists, whose aim is to discover how lexical memory is structured and organized. The facilitation process of word retrieval through semantic priming has long been studied. The present research is aimed to reveal which semantic category has the best priming effect. Through a lexical decision task experiment we compared the reaction times of masked primed pairs and unprimed pairs. In addition, we analyzed the reaction times and priming effect of connected semantic relations: antonymy, frame, synonymy, implication and verb-object. The data collected and interpreted unveiled that the mean reaction times of primed pairs were shorter than those of unprimed pairs. As to semantic priming, the most significantly primed pairs were those of implications and verb- objects, and not those of synonymy or antonymy as it might be expected.

  15. Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration.

    Science.gov (United States)

    Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

    2016-07-08

    This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) BACKGROUND: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) METHODS: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) RESULTS: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) CONCLUSION: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database.

  16. Quality of semantic standards

    NARCIS (Netherlands)

    Folmer, Erwin Johan Albert

    2012-01-01

    Little scientific literature addresses the issue of quality of semantic standards, albeit a problem with high economic and social impact. Our problem survey, including 34 semantic Standard Setting Organizations (SSOs), gives evidence that quality of standards can be improved, but for improvement a

  17. Influence of auditory spatial attention on cross-modal semantic priming effect: evidence from N400 effect.

    Science.gov (United States)

    Wang, Hongyan; Zhang, Gaoyan; Liu, Baolin

    2017-01-01

    Semantic priming is an important research topic in the field of cognitive neuroscience. Previous studies have shown that the uni-modal semantic priming effect can be modulated by attention. However, the influence of attention on cross-modal semantic priming is unclear. To investigate this issue, the present study combined a cross-modal semantic priming paradigm with an auditory spatial attention paradigm, presenting the visual pictures as the prime stimuli and the semantically related or unrelated sounds as the target stimuli. Event-related potentials results showed that when the target sound was attended to, the N400 effect was evoked. The N400 effect was also observed when the target sound was not attended to, demonstrating that the cross-modal semantic priming effect persists even though the target stimulus is not focused on. Further analyses revealed that the N400 effect evoked by the unattended sound was significantly lower than the effect evoked by the attended sound. This contrast provides new evidence that the cross-modal semantic priming effect can be modulated by attention.

  18. Morphological Cues for Lexical Semantics

    National Research Council Canada - National Science Library

    Light, Marc

    1996-01-01

    Most natural language processing tasks require lexical semantic information such as verbal argument structure and selectional restrictions, corresponding nominal semantic class, verbal aspectual class...

  19. Incremental Ontology-Based Extraction and Alignment in Semi-structured Documents

    Science.gov (United States)

    Thiam, Mouhamadou; Bennacer, Nacéra; Pernelle, Nathalie; Lô, Moussa

    SHIRIis an ontology-based system for integration of semi-structured documents related to a specific domain. The system’s purpose is to allow users to access to relevant parts of documents as answers to their queries. SHIRI uses RDF/OWL for representation of resources and SPARQL for their querying. It relies on an automatic, unsupervised and ontology-driven approach for extraction, alignment and semantic annotation of tagged elements of documents. In this paper, we focus on the Extract-Align algorithm which exploits a set of named entity and term patterns to extract term candidates to be aligned with the ontology. It proceeds in an incremental manner in order to populate the ontology with terms describing instances of the domain and to reduce the access to extern resources such as Web. We experiment it on a HTML corpus related to call for papers in computer science and the results that we obtain are very promising. These results show how the incremental behaviour of Extract-Align algorithm enriches the ontology and the number of terms (or named entities) aligned directly with the ontology increases.

  20. Language networks associated with computerized semantic indices.

    Science.gov (United States)

    Pakhomov, Serguei V S; Jones, David T; Knopman, David S

    2015-01-01

    Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. On the Existence of Semantic Working Memory: Evidence for Direct Semantic Maintenance

    Science.gov (United States)

    Shivde, Geeta; Anderson, Michael C.

    2011-01-01

    Despite widespread acknowledgment of the importance of online semantic maintenance, there has been astonishingly little work that clearly establishes this construct. We review the extant work relevant to short-term retention of meaning and show that, although consistent with semantic working memory, most data can be accommodated in other ways.…

  2. Brain and behavioural correlates of action semantic deficits in autism.

    Directory of Open Access Journals (Sweden)

    Rachel Louise Moseley

    2013-11-01

    Full Text Available Action-perception circuits comprising neurons in the motor system have been proposed as main building blocks of higher cognition; accordingly, motor dysfunction should entail cognitive deficits. Autism spectrum conditions (ASC are marked by motor impairments but the implications of such motor dysfunction for higher cognition remain unclear. We here used word reading and semantic judgement tasks to interrogate action-related motor cognition and its corresponding fMRI brain activation in high-functioning adults with ASC. These participants exhibited hypoactivity of motor cortex in language processing relative to typically developing (TD controls. Crucially, we also found a deficit in semantic processing of action-related words, which, intriguingly, significantly correlated with their underactivation of motor cortex to these items. Furthermore, the word-induced hypoactivity in the motor system also predicted the severity of ASC as expressed by the number of autistic symptoms measured by the Autism-Spectrum Quotient (Baron-Cohen et al, 2001. These significant correlations between word-induced activation of the motor system and a newly discovered semantic deficit in a condition known to be characterised by motor impairments, along with the correlation of such activation with general autistic traits confirm critical predictions of causal theories explaining cognitive and semantic deficits in ASC, in part, to dysfunctional action-perception circuits and resultant reduction of motor system activation.

  3. The BiSciCol Triplifier: bringing biodiversity data to the Semantic Web.

    Science.gov (United States)

    Stucky, Brian J; Deck, John; Conlin, Tom; Ziemba, Lukasz; Cellinese, Nico; Guralnick, Robert

    2014-07-29

    Recent years have brought great progress in efforts to digitize the world's biodiversity data, but integrating data from many different providers, and across research domains, remains challenging. Semantic Web technologies have been widely recognized by biodiversity scientists for their potential to help solve this problem, yet these technologies have so far seen little use for biodiversity data. Such slow uptake has been due, in part, to the relative complexity of Semantic Web technologies along with a lack of domain-specific software tools to help non-experts publish their data to the Semantic Web. The BiSciCol Triplifier is new software that greatly simplifies the process of converting biodiversity data in standard, tabular formats, such as Darwin Core-Archives, into Semantic Web-ready Resource Description Framework (RDF) representations. The Triplifier uses a vocabulary based on the popular Darwin Core standard, includes both Web-based and command-line interfaces, and is fully open-source software. Unlike most other RDF conversion tools, the Triplifier does not require detailed familiarity with core Semantic Web technologies, and it is tailored to a widely popular biodiversity data format and vocabulary standard. As a result, the Triplifier can often fully automate the conversion of biodiversity data to RDF, thereby making the Semantic Web much more accessible to biodiversity scientists who might otherwise have relatively little knowledge of Semantic Web technologies. Easy availability of biodiversity data as RDF will allow researchers to combine data from disparate sources and analyze them with powerful linked data querying tools. However, before software like the Triplifier, and Semantic Web technologies in general, can reach their full potential for biodiversity science, the biodiversity informatics community must address several critical challenges, such as the widespread failure to use robust, globally unique identifiers for biodiversity data.

  4. Semantic Web-based Vocabulary Broker for Open Science

    Science.gov (United States)

    Ritschel, B.; Neher, G.; Iyemori, T.; Murayama, Y.; Kondo, Y.; Koyama, Y.; King, T. A.; Galkin, I. A.; Fung, S. F.; Wharton, S.; Cecconi, B.

    2016-12-01

    Keyword vocabularies are used to tag and to identify data of science data repositories. Such vocabularies consist of controlled terms and the appropriate concepts, such as GCMD1 keywords or the ESPAS2 keyword ontology. The Semantic Web-based mash-up of domain-specific, cross- or even trans-domain vocabularies provides unique capabilities in the network of appropriate data resources. Based on a collaboration between GFZ3, the FHP4, the WDC for Geomagnetism5 and the NICT6 we developed the concept of a vocabulary broker for inter- and trans-disciplinary data detection and integration. Our prototype of the Semantic Web-based vocabulary broker uses OSF7 for the mash-up of geo and space research vocabularies, such as GCMD keywords, ESPAS keyword ontology and SPASE8 keyword vocabulary. The vocabulary broker starts the search with "free" keywords or terms of a specific vocabulary scheme. The vocabulary broker almost automatically connects the different science data repositories which are tagged by terms of the aforementioned vocabularies. Therefore the mash-up of the SKOS9 based vocabularies with appropriate metadata from different domains can be realized by addressing LOD10 resources or virtual SPARQL11 endpoints which maps relational structures into the RDF format12. In order to demonstrate such a mash-up approach in real life, we installed and use a D2RQ13 server for the integration of IUGONET14 data which are managed by a relational database. The OSF based vocabulary broker and the D2RQ platform are installed at virtual LINUX machines at the Kyoto University. The vocabulary broker meets the standard of a main component of the WDS15 knowledge network. The Web address of the vocabulary broker is http://wdcosf.kugi.kyoto-u.ac.jp 1 Global Change Master Directory2 Near earth space data infrastructure for e-science3 German Research Centre for Geosciences4 University of Applied Sciences Potsdam5 World Data Center for Geomagnetism Kyoto6 National Institute of Information and

  5. Semantic Coherence Facilitates Distributional Learning.

    Science.gov (United States)

    Ouyang, Long; Boroditsky, Lera; Frank, Michael C

    2017-04-01

    Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of association with other words (e.g., they both tend to occur with words like "deliver," "truck," "package"). In contrast to these computational results, artificial language learning experiments suggest that distributional statistics alone do not facilitate learning of linguistic categories. However, experiments in this paradigm expose participants to entirely novel words, whereas real language learners encounter input that contains some known words that are semantically organized. In three experiments, we show that (a) the presence of familiar semantic reference points facilitates distributional learning and (b) this effect crucially depends both on the presence of known words and the adherence of these known words to some semantic organization. Copyright © 2016 Cognitive Science Society, Inc.

  6. Generation of Signs within Semantic and Phonological Categories: Data from Deaf Adults and Children Who Use American Sign Language

    Science.gov (United States)

    Beal-Alvarez, Jennifer S.; Figueroa, Daileen M.

    2017-01-01

    Two key areas of language development include semantic and phonological knowledge. Semantic knowledge relates to word and concept knowledge. Phonological knowledge relates to how language parameters combine to create meaning. We investigated signing deaf adults' and children's semantic and phonological sign generation via one-minute tasks,…

  7. Episodic and Semantic Autobiographical Memory and Everyday Memory during Late Childhood and Early Adolescence.

    Science.gov (United States)

    Willoughby, Karen A; Desrocher, Mary; Levine, Brian; Rovet, Joanne F

    2012-01-01

    Few studies have examined both episodic and semantic autobiographical memory (AM) performance during late childhood and early adolescence. Using the newly developed Children's Autobiographical Interview (CAI), the present study examined the effects of age and sex on episodic and semantic AM and everyday memory in 182 children and adolescents. Results indicated that episodic and semantic AM both improved between 8 and 16 years of age; however, age-related changes were larger for episodic AM than for semantic AM. In addition, females were found to recall more episodic AM details, but not more semantic AM details, than males. Importantly, this sex difference in episodic AM recall was attenuated under conditions of high retrieval support (i.e., the use of probing questions). The ability to clearly visualize past events at the time of recollection was related to children's episodic AM recall performance, particularly the retrieval of perceptual details. Finally, similar age and sex effects were found between episodic AM and everyday memory ability (e.g., memory for everyday activities). More specifically, older participants and females exhibited better episodic AM and everyday memory performance than younger participants and males. Overall, the present study provides important new insight into both episodic and semantic AM performance, as well as the relation between episodic AM and everyday memory, during late childhood and adolescence.

  8. Episodic and Semantic Autobiographical Memory and Everyday Memory during Late Childhood and Early Adolescence

    Science.gov (United States)

    Willoughby, Karen A.; Desrocher, Mary; Levine, Brian; Rovet, Joanne F.

    2012-01-01

    Few studies have examined both episodic and semantic autobiographical memory (AM) performance during late childhood and early adolescence. Using the newly developed Children’s Autobiographical Interview (CAI), the present study examined the effects of age and sex on episodic and semantic AM and everyday memory in 182 children and adolescents. Results indicated that episodic and semantic AM both improved between 8 and 16 years of age; however, age-related changes were larger for episodic AM than for semantic AM. In addition, females were found to recall more episodic AM details, but not more semantic AM details, than males. Importantly, this sex difference in episodic AM recall was attenuated under conditions of high retrieval support (i.e., the use of probing questions). The ability to clearly visualize past events at the time of recollection was related to children’s episodic AM recall performance, particularly the retrieval of perceptual details. Finally, similar age and sex effects were found between episodic AM and everyday memory ability (e.g., memory for everyday activities). More specifically, older participants and females exhibited better episodic AM and everyday memory performance than younger participants and males. Overall, the present study provides important new insight into both episodic and semantic AM performance, as well as the relation between episodic AM and everyday memory, during late childhood and adolescence. PMID:22403560

  9. Extent and neural basis of semantic memory impairment in mild cognitive impairment.

    Science.gov (United States)

    Barbeau, Emmanuel J; Didic, Mira; Joubert, Sven; Guedj, Eric; Koric, Lejla; Felician, Olivier; Ranjeva, Jean-Philippe; Cozzone, Patrick; Ceccaldi, Mathieu

    2012-01-01

    An increasing number of studies indicate that semantic memory is impaired in mild cognitive impairment (MCI). However, the extent and the neural basis of this impairment remain unknown. The aim of the present study was: 1) to evaluate whether all or only a subset of semantic domains are impaired in MCI patients; and 2) to assess the neural substrate of the semantic impairment in MCI patients using voxel-based analysis of MR grey matter density and SPECT perfusion. 29 predominantly amnestic MCI patients and 29 matched control subjects participated in this study. All subjects underwent a full neuropsychological assessment, along with a battery of five tests evaluating different domains of semantic memory. A semantic memory composite Z-score was established on the basis of this battery and was correlated with MRI grey matter density and SPECT perfusion measures. MCI patients were found to have significantly impaired performance across all semantic tasks, in addition to their anterograde memory deficit. Moreover, no temporal gradient was found for famous faces or famous public events and knowledge for the most remote decades was also impaired. Neuroimaging analyses revealed correlations between semantic knowledge and perirhinal/entorhinal areas as well as the anterior hippocampus. Therefore, the deficits in the realm of semantic memory in patients with MCI is more widespread than previously thought and related to dysfunction of brain areas beyond the limbic-diencephalic system involved in episodic memory. The severity of the semantic impairment may indicate a decline of semantic memory that began many years before the patients first consulted.

  10. Operationalizing Semantic Medline for meeting the information needs at point of care

    Science.gov (United States)

    Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

    2015-01-01

    Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible. PMID:26306259

  11. Operationalizing Semantic Medline for meeting the information needs at point of care.

    Science.gov (United States)

    Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

    2015-01-01

    Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible.

  12. A hybrid model based on neural networks for biomedical relation extraction.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Zhang, Shaowu; Sun, Yuanyuan; Yang, Liang

    2018-05-01

    Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutional neural networks (CNNs) are two major neural network models for biomedical relation extraction. Neural network-based methods for biomedical relation extraction typically focus on the sentence sequence and employ RNNs or CNNs to learn the latent features from sentence sequences separately. However, RNNs and CNNs have their own advantages for biomedical relation extraction. Combining RNNs and CNNs may improve biomedical relation extraction. In this paper, we present a hybrid model for the extraction of biomedical relations that combines RNNs and CNNs. First, the shortest dependency path (SDP) is generated based on the dependency graph of the candidate sentence. To make full use of the SDP, we divide the SDP into a dependency word sequence and a relation sequence. Then, RNNs and CNNs are employed to automatically learn the features from the sentence sequence and the dependency sequences, respectively. Finally, the output features of the RNNs and CNNs are combined to detect and extract biomedical relations. We evaluate our hybrid model using five public (protein-protein interaction) PPI corpora and a (drug-drug interaction) DDI corpus. The experimental results suggest that the advantages of RNNs and CNNs in biomedical relation extraction are complementary. Combining RNNs and CNNs can effectively boost biomedical relation extraction performance. Copyright © 2018 Elsevier Inc. All rights reserved.

  13. Pragmatics for formal semantics

    DEFF Research Database (Denmark)

    Danvy, Olivier

    2011-01-01

    This tech talk describes how to write and how to inter-derive formal semantics for sequential programming languages. The progress reported here is (1) concrete guidelines to write each formal semantics to alleviate their proof obligations, and (2) simple calculational tools to obtain a formal...

  14. A reasonable Semantic Web

    NARCIS (Netherlands)

    Hitzler, Pascal; Van Harmelen, Frank

    2010-01-01

    The realization of Semantic Web reasoning is central to substantiating the Semantic Web vision. However, current mainstream research on this topic faces serious challenges, which forces us to question established lines of research and to rethink the underlying approaches. We argue that reasoning for

  15. A trade-off between local and distributed information processing associated with remote episodic versus semantic memory.

    Science.gov (United States)

    Heisz, Jennifer J; Vakorin, Vasily; Ross, Bernhard; Levine, Brian; McIntosh, Anthony R

    2014-01-01

    Episodic memory and semantic memory produce very different subjective experiences yet rely on overlapping networks of brain regions for processing. Traditional approaches for characterizing functional brain networks emphasize static states of function and thus are blind to the dynamic information processing within and across brain regions. This study used information theoretic measures of entropy to quantify changes in the complexity of the brain's response as measured by magnetoencephalography while participants listened to audio recordings describing past personal episodic and general semantic events. Personal episodic recordings evoked richer subjective mnemonic experiences and more complex brain responses than general semantic recordings. Critically, we observed a trade-off between the relative contribution of local versus distributed entropy, such that personal episodic recordings produced relatively more local entropy whereas general semantic recordings produced relatively more distributed entropy. Changes in the relative contributions of local and distributed entropy to the total complexity of the system provides a potential mechanism that allows the same network of brain regions to represent cognitive information as either specific episodes or more general semantic knowledge.

  16. Gricean Semantics and Vague Speaker-Meaning

    OpenAIRE

    Schiffer, Stephen

    2017-01-01

    Presentations of Gricean semantics, including Stephen Neale’s in “Silent Reference,” totally ignore vagueness, even though virtually every utterance is vague. I ask how Gricean semantics might be adjusted to accommodate vague speaker-meaning. My answer is that it can’t accommodate it: the Gricean program collapses in the face of vague speaker-meaning. The Gricean might, however, fi nd some solace in knowing that every other extant meta-semantic and semantic program is in the same boat.

  17. Modeling the Interaction Between Semantic Agents and Semantic Web Services Using MDA Approach

    NARCIS (Netherlands)

    Kardas, Geylani; Göknil, Arda; Dikenelli, Oguz; Topaloglu, N. Yasemin

    2007-01-01

    In this paper, we present our metamodeling approach for integrating semantic web services and semantic web enabled agents under Model Driven Architecture (MDA) view which defines a conceptual framework to realize model driven development. We believe that agents must have well designed environment

  18. Reliability in content analysis: The case of semantic feature norms classification.

    Science.gov (United States)

    Bolognesi, Marianna; Pilgram, Roosmaryn; van den Heerik, Romy

    2017-12-01

    Semantic feature norms (e.g., STIMULUS: car → RESPONSE: ) are commonly used in cognitive psychology to look into salient aspects of given concepts. Semantic features are typically collected in experimental settings and then manually annotated by the researchers into feature types (e.g., perceptual features, taxonomic features, etc.) by means of content analyses-that is, by using taxonomies of feature types and having independent coders perform the annotation task. However, the ways in which such content analyses are typically performed and reported are not consistent across the literature. This constitutes a serious methodological problem that might undermine the theoretical claims based on such annotations. In this study, we first offer a review of some of the released datasets of annotated semantic feature norms and the related taxonomies used for content analysis. We then provide theoretical and methodological insights in relation to the content analysis methodology. Finally, we apply content analysis to a new dataset of semantic features and show how the method should be applied in order to deliver reliable annotations and replicable coding schemes. We tackle the following issues: (1) taxonomy structure, (2) the description of categories, (3) coder training, and (4) sustainability of the coding scheme-that is, comparison of the annotations provided by trained versus novice coders. The outcomes of the project are threefold: We provide methodological guidelines for semantic feature classification; we provide a revised and adapted taxonomy that can (arguably) be applied to both concrete and abstract concepts; and we provide a dataset of annotated semantic feature norms.

  19. Speaker information affects false recognition of unstudied lexical-semantic associates.

    Science.gov (United States)

    Luthra, Sahil; Fox, Neal P; Blumstein, Sheila E

    2018-05-01

    Recognition of and memory for a spoken word can be facilitated by a prior presentation of that word spoken by the same talker. However, it is less clear whether this speaker congruency advantage generalizes to facilitate recognition of unheard related words. The present investigation employed a false memory paradigm to examine whether information about a speaker's identity in items heard by listeners could influence the recognition of novel items (critical intruders) phonologically or semantically related to the studied items. In Experiment 1, false recognition of semantically associated critical intruders was sensitive to speaker information, though only when subjects attended to talker identity during encoding. Results from Experiment 2 also provide some evidence that talker information affects the false recognition of critical intruders. Taken together, the present findings indicate that indexical information is able to contact the lexical-semantic network to affect the processing of unheard words.

  20. A Structural-Lexical Measure of Semantic Similarity for Geo-Knowledge Graphs

    Directory of Open Access Journals (Sweden)

    Andrea Ballatore

    2015-04-01

    Full Text Available Graphs have become ubiquitous structures to encode geographic knowledge online. The Semantic Web’s linked open data, folksonomies, wiki websites and open gazetteers can be seen as geo-knowledge graphs, that is labeled graphs whose vertices represent geographic concepts and whose edges encode the relations between concepts. To compute the semantic similarity of concepts in such structures, this article defines the network-lexical similarity measure (NLS. This measure estimates similarity by combining two complementary sources of information: the network similarity of vertices and the semantic similarity of the lexical definitions. NLS is evaluated on the OpenStreetMap Semantic Network, a crowdsourced geo-knowledge graph that describes geographic concepts. The hybrid approach outperforms both network and lexical measures, obtaining very strong correlation with the similarity judgments of human subjects.