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.

    Science.gov (United States)

    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. 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

  4. Semantic Location Extraction from Crowdsourced Data

    Science.gov (United States)

    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. Exploring DBpedia and Wikipedia for Portuguese Semantic Relationship Extraction

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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).

  9. 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.

  10. 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.

  11. The methodology of semantic analysis for extracting physical effects

    Science.gov (United States)

    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.

  12. 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.

  13. 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...

  14. 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...

  15. Algorithmic Procedure for Finding Semantically Related Journals.

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    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…

  16. Spatial Relation Predicates in Topographic Feature Semantics

    Science.gov (United States)

    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.

  17. 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

  18. Semantic feature extraction for interior environment understanding and retrieval

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

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

    Science.gov (United States)

    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.

  4. 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…

  5. 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.

  6. 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,

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

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    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…

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

    Science.gov (United States)

    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.

  9. 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…

  10. 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...

  11. 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…

  12. 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...

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

    Directory of Open Access Journals (Sweden)

    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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

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

    Science.gov (United States)

    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.

  20. Semantics-based information extraction for detecting economic events

    NARCIS (Netherlands)

    A.C. Hogenboom (Alexander); F. Frasincar (Flavius); K. Schouten (Kim); O. van der Meer

    2013-01-01

    textabstractAs today's financial markets are sensitive to breaking news on economic events, accurate and timely automatic identification of events in news items is crucial. Unstructured news items originating from many heterogeneous sources have to be mined in order to extract knowledge useful for

  1. 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.

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

    Science.gov (United States)

    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.

  3. Spoken Language Understanding Systems for Extracting Semantic Information from Speech

    CERN Document Server

    Tur, Gokhan

    2011-01-01

    Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, usin

  4. 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.

  5. 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...

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

    Science.gov (United States)

    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.

  7. 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:…

  8. 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.

  9. 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...

  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. 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.…

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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...

  5. Incremental Observer Relative Data Extraction

    DEFF Research Database (Denmark)

    Bukauskas, Linas; Bøhlen, Michael Hanspeter

    2004-01-01

    The visual exploration of large databases calls for a tight coupling of database and visualization systems. Current visualization systems typically fetch all the data and organize it in a scene tree that is then used to render the visible data. For immersive data explorations in a Cave...... or a Panorama, where an observer is data space this approach is far from optimal. A more scalable approach is to make the observer-aware database system and to restrict the communication between the database and visualization systems to the relevant data. In this paper VR-tree, an extension of the R......-tree, is used to index visibility ranges of objects. We introduce a new operator for incremental Observer Relative data Extraction (iORDE). We propose the Volatile Access STructure (VAST), a lightweight main memory structure that is created on the fly and is maintained during visual data explorations. VAST...

  6. 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.

  7. 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…

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. 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...

  13. 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

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

    Science.gov (United States)

    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.

  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. 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.

  17. 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.

  18. 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.

  19. [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

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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...

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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...

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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...

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  4. 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.

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

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    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. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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).

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

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    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.

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. Memory for semantically related and unrelated declarative information: the benefit of sleep, the cost of wake.

    Directory of Open Access Journals (Sweden)

    Jessica D Payne

    Full Text Available Numerous studies have examined sleep's influence on a range of hippocampus-dependent declarative memory tasks, from text learning to spatial navigation. In this study, we examined the impact of sleep, wake, and time-of-day influences on the processing of declarative information with strong semantic links (semantically related word pairs and information requiring the formation of novel associations (unrelated word pairs. Participants encoded a set of related or unrelated word pairs at either 9 am or 9 pm, and were then tested after an interval of 30 min, 12 hr, or 24 hr. The time of day at which subjects were trained had no effect on training performance or initial memory of either word pair type. At 12 hr retest, memory overall was superior following a night of sleep compared to a day of wakefulness. However, this performance difference was a result of a pronounced deterioration in memory for unrelated word pairs across wake; there was no sleep-wake difference for related word pairs. At 24 hr retest, with all subjects having received both a full night of sleep and a full day of wakefulness, we found that memory was superior when sleep occurred shortly after learning rather than following a full day of wakefulness. Lastly, we present evidence that the rate of deterioration across wakefulness was significantly diminished when a night of sleep preceded the wake period compared to when no sleep preceded wake, suggesting that sleep served to stabilize the memories against the deleterious effects of subsequent wakefulness. Overall, our results demonstrate that 1 the impact of 12 hr of waking interference on memory retention is strongly determined by word-pair type, 2 sleep is most beneficial to memory 24 hr later if it occurs shortly after learning, and 3 sleep does in fact stabilize declarative memories, diminishing the negative impact of subsequent wakefulness.

  1. 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

  2. Extraction of gravitational waves in numerical relativity.

    Science.gov (United States)

    Bishop, Nigel T; Rezzolla, Luciano

    2016-01-01

    A numerical-relativity calculation yields in general a solution of the Einstein equations including also a radiative part, which is in practice computed in a region of finite extent. Since gravitational radiation is properly defined only at null infinity and in an appropriate coordinate system, the accurate estimation of the emitted gravitational waves represents an old and non-trivial problem in numerical relativity. A number of methods have been developed over the years to "extract" the radiative part of the solution from a numerical simulation and these include: quadrupole formulas, gauge-invariant metric perturbations, Weyl scalars, and characteristic extraction. We review and discuss each method, in terms of both its theoretical background as well as its implementation. Finally, we provide a brief comparison of the various methods in terms of their inherent advantages and disadvantages.

  3. Transfer Learning for Adaptive Relation Extraction

    Science.gov (United States)

    2011-09-13

    sequences. Second, the restriction to the correct 3Automatic Content Extraction http://www.itl.nist.gov/iad/mig/tests/ace/ 21 Relation Candidate...the weight vector is chosen to be ~λ∗ = arg max ~λ [Πni=1 logP~λ(yi|xi)− m∑ i=1 λ2 2σ2 ] , where σ controls the degree of regularization. Maximizing the

  4. Event-related brain potentials in memory: correlates of episodic, semantic and implicit memory.

    Science.gov (United States)

    Wieser, Stephan; Wieser, Heinz Gregor

    2003-06-01

    To study cognitive evoked potentials, recorded from scalp EEG and foramen ovale electrodes, during activation of explicit and implicit memory. The subgroups of explicit memory, episodic and semantic memory, are looked at separately. A word-learning task was used, which has been shown to activate hippocampus in H(2)(15)O positron emission tomography studies. Subjects had to study and remember word pairs using different learning strategies: (i) associative word learning (AWL), which activates the episodic memory, (ii) deep single word encoding (DSWE), which activates the semantic memory, and (iii) shallow single word encoding (SSWE), which activates the implicit memory and serves as a baseline. The test included the 'remember/know' paradigm as a behavioural learning control. During the task condition, a 10-20 scalp EEG with additional electrodes in both temporal lobes regions was recorded from 11 healthy volunteers. In one patient with mesiotemporal lobe epilepsy, the EEG was recorded from bilateral foramen ovale electrodes directly from mesial temporal lobe structures. Event-related potentials (ERPs) were calculated off-line and visual and statistical analyses were made. Associative learning strategy produced the best memory performance and the best noetic awareness experience, whereas shallow single word encoding produced the worst performance and the smallest noetic awareness. Deep single word encoding performance was in between. ERPs differed according to the test condition, during both encoding and retrieval, from both the scalp EEG and the foramen ovale electrode recordings. Encoding showed significant differences between the shallow single word encoding (SSWE), which is mainly a function of graphical characteristics, and the other two strategies, deep single word (DSWE) and associative learning (AWL), in which there is a semantic processing of the meaning. ERPs generated by these two categories, which are both functions of explicit memory, differed as well

  5. 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

  6. 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.

  7. 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

  8. 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…

  9. 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

  10. 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

  11. 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.

  12. RGFinder: a system for determining semantically related genes using GO graph minimum spanning tree.

    Science.gov (United States)

    Taha, Kamal

    2015-01-01

    Biologists often need to know the set S' of genes that are the most functionally and semantically related to a given set S of genes. For determining the set S', most current gene similarity measures overlook the structural dependencies among the Gene Ontology (GO) terms annotating the set S, which may lead to erroneous results. We introduce in this paper a biological search engine called RGFinder that considers the structural dependencies among GO terms by employing the concept of existence dependency. RGFinder assigns a weight to each edge in GO graph to represent the degree of relatedness between the two GO terms connected by the edge. The value of the weight is determined based on the following factors: 1) type of the relation represented by the edge (e.g., an "is-a" relation is assigned a different weight than a "part-of" relation), 2) the functional relationship between the two GO terms connected by the edge, and 3) the string-substring relationship between the names of the two GO terms connected by the edge. RGFinder then constructs a minimum spanning tree of GO graph based on these weights. In the framework of RGFinder, the set S' is annotated to the GO terms located at the lowest convergences of the subtree of the minimum spanning tree that passes through the GO terms annotating set S. We evaluated RGFinder experimentally and compared it with four gene set enrichment systems. Results showed marked improvement.

  13. 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/.

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Disease causality extraction based on lexical semantics and document-clause frequency from biomedical literature.

    Science.gov (United States)

    Lee, Dong-Gi; Shin, Hyunjung

    2017-05-18

    Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this paper, we propose a causal disease network that implements disease causality through text mining on biomedical literature. To identify the causality between diseases, the proposed method includes two schemes: the first is the lexicon-based causality term strength, which provides the causal strength on a variety of causality terms based on lexicon analysis. The second is the frequency-based causality strength, which determines the direction and strength of causality based on document and clause frequencies in the literature. We applied the proposed method to 6,617,833 PubMed literature, and chose 195 diseases to construct a causal disease network. From all possible pairs of disease nodes in the network, 1011 causal pairs of 149 diseases were extracted. The resulting network was compared with that of a previous study. In terms of both coverage and quality, the proposed method showed outperforming results; it determined 2.7 times more causalities and showed higher correlation with associated diseases than the existing method. This research has novelty in which the proposed method circumvents the limitations of time and cost in applying all possible causalities in biological experiments and it is a more advanced text mining technique by defining the concepts of causality term strength.

  1. 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.

  2. 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.

  3. A Domain Independent Framework for Extracting Linked Semantic Data from Tables

    Science.gov (United States)

    2012-01-01

    queda, J ., Ezzat, A.: A survey of current approaches for mapping of relational databases to rdf. Tech. rep., W3C (2009) 24. Salton , G., Mcgill, M.J...Once again ψ2 will assign a score to each entity which can be used to rank the entities. Thus, ψ2 = exp(w T 2 .f2(Ri, j , Ei, j )) where w2 is the weight...vector, Ei, j is the candidate entity and Ri, j is string value in column i and row j . The feature vector f2 is composed as follows: f2

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

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

    Science.gov (United States)

    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.

  10. How doctors apply semantic components to specify search in work-related information retrieval

    DEFF Research Database (Denmark)

    Lykke, Marianne; Price, Susan L.; Delcambre, Lois L. M.

    2012-01-01

    Workplace searching is often context-specific and targets a “right answer” within some domain-specific aspect of the search topic. We have developed the semantic component (SC) model that allows searchers to specify a search within context-specific aspects of the main topic of documents. The goal...

  11. 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,

  12. 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…

  13. 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.

  14. 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

  15. Categorizing words through semantic memory navigation

    Science.gov (United States)

    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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Legacy2Drupal - Conversion of an existing oceanographic relational database to a semantically enabled Drupal content management system

    Science.gov (United States)

    Maffei, A. R.; Chandler, C. L.; Work, T.; Allen, J.; Groman, R. C.; Fox, P. A.

    2009-12-01

    Content Management Systems (CMSs) provide powerful features that can be of use to oceanographic (and other geo-science) data managers. However, in many instances, geo-science data management offices have previously designed customized schemas for their metadata. The WHOI Ocean Informatics initiative and the NSF funded Biological Chemical and Biological Data Management Office (BCO-DMO) have jointly sponsored a project to port an existing, relational database containing oceanographic metadata, along with an existing interface coded in Cold Fusion middleware, to a Drupal6 Content Management System. The goal was to translate all the existing database tables, input forms, website reports, and other features present in the existing system to employ Drupal CMS features. The replacement features include Drupal content types, CCK node-reference fields, themes, RDB, SPARQL, workflow, and a number of other supporting modules. Strategic use of some Drupal6 CMS features enables three separate but complementary interfaces that provide access to oceanographic research metadata via the MySQL database: 1) a Drupal6-powered front-end; 2) a standard SQL port (used to provide a Mapserver interface to the metadata and data; and 3) a SPARQL port (feeding a new faceted search capability being developed). Future plans include the creation of science ontologies, by scientist/technologist teams, that will drive semantically-enabled faceted search capabilities planned for the site. Incorporation of semantic technologies included in the future Drupal 7 core release is also anticipated. Using a public domain CMS as opposed to proprietary middleware, and taking advantage of the many features of Drupal 6 that are designed to support semantically-enabled interfaces will help prepare the BCO-DMO database for interoperability with other ecosystem databases.

  1. 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

  2. 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.

  3. 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

  4. Semantics of Islam and Quran and it’s Relation with Religious Pluralism

    Directory of Open Access Journals (Sweden)

    Javad Mohammadi

    2013-02-01

    Full Text Available This research attempts to consider the relationship between "Islam" And "religious pluralism" through lexical and Quranic semantic of "Islam ". This word derived from "Selm" in Arabic and means subordination, humility and submission, because it does not have any insubordination and refusal. In Quranic verses " Islam" means "being surrendered to God and his commands", the commands that transmitted to people by messengers of God. Therefore, according to the verses of noble Quran, one of the most important submission conditions is the belief that Prophet Muhammad (pbuh, is the messenger of God. This reading is consistent with a meaning of the religious pluralism that emphasizes on rightfulness of Islam along the salvation of non Muslim people and , also, peaceful life with them, while is inconsistent with the definition that believe in plurality and equality of religions in rightfulness .

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Archive of Census Related Products (ACRP): 1990 Standard Extract Files

    Data.gov (United States)

    National Aeronautics and Space Administration — The 1990 Standard Extract Files portion of the Archive of Census Related Products (ACRP) contains population and housing data derived from the U.S. Census Bureau's...

  10. Accelerator Technology: Injection and Extraction Related Hardware: Kickers and Septa

    CERN Document Server

    Barnes, M J; Mertens, V

    2013-01-01

    This document is part of Subvolume C 'Accelerators and Colliders' of Volume 21 'Elementary Particles' of Landolt-Börnstein - Group I 'Elementary Particles, Nuclei and Atoms'. It contains the the Section '8.7 Injection and Extraction Related Hardware: Kickers and Septa' of the Chapter '8 Accelerator Technology' with the content: 8.7 Injection and Extraction Related Hardware: Kickers and Septa 8.7.1 Fast Pulsed Systems (Kickers) 8.7.2 Electrostatic and Magnetic Septa

  11. Social network extraction based on Web: 1. Related superficial methods

    Science.gov (United States)

    Khairuddin Matyuso Nasution, Mahyuddin

    2018-01-01

    Often the nature of something affects methods to resolve the related issues about it. Likewise, methods to extract social networks from the Web, but involve the structured data types differently. This paper reveals several methods of social network extraction from the same sources that is Web: the basic superficial method, the underlying superficial method, the description superficial method, and the related superficial methods. In complexity we derive the inequalities between methods and so are their computations. In this case, we find that different results from the same tools make the difference from the more complex to the simpler: Extraction of social network by involving co-occurrence is more complex than using occurrences.

  12. Empirical study using network of semantically related associations in bridging the knowledge gap.

    Science.gov (United States)

    Abedi, Vida; Yeasin, Mohammed; Zand, Ramin

    2014-11-27

    The data overload has created a new set of challenges in finding meaningful and relevant information with minimal cognitive effort. However designing robust and scalable knowledge discovery systems remains a challenge. Recent innovations in the (biological) literature mining tools have opened new avenues to understand the confluence of various diseases, genes, risk factors as well as biological processes in bridging the gaps between the massive amounts of scientific data and harvesting useful knowledge. In this paper, we highlight some of the findings using a text analytics tool, called ARIANA--Adaptive Robust and Integrative Analysis for finding Novel Associations. Empirical study using ARIANA reveals knowledge discovery instances that illustrate the efficacy of such tool. For example, ARIANA can capture the connection between the drug hexamethonium and pulmonary inflammation and fibrosis that caused the tragic death of a healthy volunteer in a 2001 John Hopkins asthma study, even though the abstract of the study was not part of the semantic model. An integrated system, such as ARIANA, could assist the human expert in exploratory literature search by bringing forward hidden associations, promoting data reuse and knowledge discovery as well as stimulating interdisciplinary projects by connecting information across the disciplines.

  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. 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.

  15. 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.

  16. Chemical-induced disease relation extraction with various linguistic features.

    Science.gov (United States)

    Gu, Jinghang; Qian, Longhua; Zhou, Guodong

    2016-01-01

    Understanding the relations between chemicals and diseases is crucial in various biomedical tasks such as new drug discoveries and new therapy developments. While manually mining these relations from the biomedical literature is costly and time-consuming, such a procedure is often difficult to keep up-to-date. To address these issues, the BioCreative-V community proposed a challenging task of automatic extraction of chemical-induced disease (CID) relations in order to benefit biocuration. This article describes our work on the CID relation extraction task on the BioCreative-V tasks. We built a machine learning based system that utilized simple yet effective linguistic features to extract relations with maximum entropy models. In addition to leveraging various features, the hypernym relations between entity concepts derived from the Medical Subject Headings (MeSH)-controlled vocabulary were also employed during both training and testing stages to obtain more accurate classification models and better extraction performance, respectively. We demoted relation extraction between entities in documents to relation extraction between entity mentions. In our system, pairs of chemical and disease mentions at both intra- and inter-sentence levels were first constructed as relation instances for training and testing, then two classification models at both levels were trained from the training examples and applied to the testing examples. Finally, we merged the classification results from mention level to document level to acquire final relations between chemicals and diseases. Our system achieved promisingF-scores of 60.4% on the development dataset and 58.3% on the test dataset using gold-standard entity annotations, respectively. Database URL:https://github.com/JHnlp/BC5CIDTask. © The Author(s) 2016. Published by Oxford University Press.

  17. 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

  18. Supporting Better Treatments for Meeting Health Consumers' Needs: Extracting Semantics in Social Data for Representing a Consumer Health Ontology

    Science.gov (United States)

    Choi, Yunseon

    2016-01-01

    Introduction: The purpose of this paper is to provide a framework for building a consumer health ontology using social tags. This would assist health users when they are accessing health information and increase the number of documents relevant to their needs. Methods: In order to extract concepts from social tags, this study conducted an…

  19. Automatic sentence extraction for the detection of scientific paper relations

    Science.gov (United States)

    Sibaroni, Y.; Prasetiyowati, S. S.; Miftachudin, M.

    2018-03-01

    The relations between scientific papers are very useful for researchers to see the interconnection between scientific papers quickly. By observing the inter-article relationships, researchers can identify, among others, the weaknesses of existing research, performance improvements achieved to date, and tools or data typically used in research in specific fields. So far, methods that have been developed to detect paper relations include machine learning and rule-based methods. However, a problem still arises in the process of sentence extraction from scientific paper documents, which is still done manually. This manual process causes the detection of scientific paper relations longer and inefficient. To overcome this problem, this study performs an automatic sentences extraction while the paper relations are identified based on the citation sentence. The performance of the built system is then compared with that of the manual extraction system. The analysis results suggested that the automatic sentence extraction indicates a very high level of performance in the detection of paper relations, which is close to that of manual sentence extraction.

  20. Semantic Songket Image Search with Cultural Computing of Symbolic Meaning Extraction and Analytical Aggregation of Color and Shape Features

    Directory of Open Access Journals (Sweden)

    Desi Amirullah

    2015-06-01

    Full Text Available The term "Songket" comes from the Malay word "Sungkit", which means "to hook" or "to gouge". Every motifs names and variations was derived from plants and animals as source of inspiration to create many patterns of songket. Each of songket patterns have a philosophy in form of rhyme that refers to the nature of the sources of songket patterns and that philosophy reflects to the beliefs and values of Malay culture. In this research, we propose a system to facilitate an understanding of songket and the philosophy as a way to conserve Songket culture. We propose a system which is able to collect information in image songket motif variations based on feature extraction methods. On each image songket motif variations, we extracted philosophy of rhyme into impressions, and extracting color features of songket images using a histogram 3D-Color Vector quantization (3D-CVQ, shape feature extraction songket image using HU Moment invariants. Then, we created an image search based on impressions, and impressions search based on image. We use techniques of search based on color, shape and aggregation (combination of colors and shapes. The experiment using impression as query : 1 Result based on color, the average value of true 7.3, total score 41.9, 2 Result based on shape, the average value of true 3, total score 16.4, 3 Result based on aggregation, the average value of true 3, total score 17.4. While based using Image Query : 1 Result based on color, the average precision 95%, 2 Result based on shape, average precision 43.3%, 3 Based aggregation, the average precision 73.3%. From our experiments, it can be concluded that the best search system using query impression and query image is based on the color. Keyword : Image Search, Philosophy, impression, Songket, cultural computing, Feature Extraction, Analytical aggregation.

  1. 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.

  2. 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....

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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...

  9. 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.

  10. 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.

  11. 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.

  12. 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)

  13. Development and validation of a set of German stimulus- and target words for an attachment related semantic priming paradigm.

    Directory of Open Access Journals (Sweden)

    Anke Maatz

    Full Text Available Experimental research in adult attachment theory is faced with the challenge to adequately activate the adult attachment system. In view of the multitude of methods employed for this purpose so far, this paper suggests to further make use of the methodological advantages of semantic priming. In order to enable the use of such a paradigm in a German speaking context, a set of German words belonging to the semantic categories 'interpersonal closeness', 'interpersonal distance' and 'neutral' were identified and their semantics were validated combining production- and rating method. 164 university students answered corresponding online-questionnaires. Ratings were analysed using analysis of variance (ANOVA and cluster analysis from which three clearly distinct groups emerged. Beyond providing validated stimulus- and target words which can be used to activate the adult attachment system in a semantic priming paradigm, the results of this study point at important links between attachment and stress which call for further investigation in the future.

  14. 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

  15. 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.

  16. 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.

  17. Semantics of trace relations in requirements models for consistency checking and inferencing

    NARCIS (Netherlands)

    Göknil, Arda; Ivanov, Ivan; van den Berg, Klaas; Veldhuis, Jan-Willem

    2009-01-01

    Requirements traceability is the ability to relate requirements back to stakeholders and forward to corresponding design artifacts, code, and test cases. Although considerable research has been devoted to relating requirements in both forward and backward directions, less attention has been paid to

  18. Generative Semantics

    Science.gov (United States)

    Bagha, Karim Nazari

    2011-01-01

    Generative semantics is (or perhaps was) a research program within linguistics, initiated by the work of George Lakoff, John R. Ross, Paul Postal and later McCawley. The approach developed out of transformational generative grammar in the mid 1960s, but stood largely in opposition to work by Noam Chomsky and his students. The nature and genesis of…

  19. Inferentializing Semantics

    Czech Academy of Sciences Publication Activity Database

    Peregrin, Jaroslav

    2010-01-01

    Roč. 39, č. 3 (2010), s. 255-274 ISSN 0022-3611 R&D Projects: GA ČR(CZ) GA401/07/0904 Institutional research plan: CEZ:AV0Z90090514 Keywords : inference * proof theory * model theory * inferentialism * semantics Subject RIV: AA - Philosophy ; Religion

  20. Abnormal self-schema in semantic memory in major depressive disorder: Evidence from event-related brain potentials.

    Science.gov (United States)

    Kiang, Michael; Farzan, Faranak; Blumberger, Daniel M; Kutas, Marta; McKinnon, Margaret C; Kansal, Vinay; Rajji, Tarek K; Daskalakis, Zafiris J

    2017-05-01

    An overly negative self-schema is a proposed cognitive mechanism of major depressive disorder (MDD). Self-schema - one's core conception of self, including how strongly one believes one possesses various characteristics - is part of semantic memory (SM), our knowledge about concepts and their relationships. We used the N400 event-related potential (ERP) - elicited by meaningful stimuli, and reduced by greater association of the stimulus with preceding context - to measure association strength between self-concept and positive, negative, and neutral characteristics in SM. ERPs were recorded from MDD patients (n=16) and controls (n=16) who viewed trials comprising a self-referential phrase followed by a positive, negative, or neutral adjective. Participants' task was to indicate via button-press whether or not they felt each adjective described themselves. Controls endorsed more positive adjectives than did MDD patients, but the opposite was true for negative adjectives. Patients had smaller N400s than controls specifically for negative adjectives, suggesting that MDD is associated with stronger than normal functional neural links between self-concept and negative characteristics in SM. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. 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

  2. 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...

  3. The Discourse Semantics of Attitudinal Relations: Continuing the Study of Lexis

    Directory of Open Access Journals (Sweden)

    Дж Р Мартин

    2017-12-01

    Full Text Available This paper explores some aspects of the problem of categorizing attitudinal relations in English, as part of a description of evaluation informed by systemic functional linguistics (SFL - appraisal. It reviews paradigmatic and syntagmatic orientations to lexis within this tradition, and the development of typological and topological representations of systemic relations. Corpus based argumentation is considered in relation to work on evaluation by Bednarek 2008; and proposals for continuing the study of lexis are suggested, focusing on resources for negotiating sadness and negative reactions to behavior (e.g. embarrassed , ashamed and the affordances of topological representation. The paper highlights the possibilities and challenges involved in continuing the study of lexis in descriptions using SFL as their informing theory.

  4. Individual differences in algebraic cognition: Relation to the approximate number and semantic memory systems.

    Science.gov (United States)

    Geary, David C; Hoard, Mary K; Nugent, Lara; Rouder, Jeffrey N

    2015-12-01

    The relation between performance on measures of algebraic cognition and acuity of the approximate number system (ANS) and memory for addition facts was assessed for 171 ninth graders (92 girls) while controlling for parental education, sex, reading achievement, speed of numeral processing, fluency of symbolic number processing, intelligence, and the central executive component of working memory. The algebraic tasks assessed accuracy in placing x,y pairs in the coordinate plane, speed and accuracy of expression evaluation, and schema memory for algebra equations. ANS acuity was related to accuracy of placements in the coordinate plane and expression evaluation but not to schema memory. Frequency of fact retrieval errors was related to schema memory but not to coordinate plane or expression evaluation accuracy. The results suggest that the ANS may contribute to or be influenced by spatial-numerical and numerical-only quantity judgments in algebraic contexts, whereas difficulties in committing addition facts to long-term memory may presage slow formation of memories for the basic structure of algebra equations. More generally, the results suggest that different brain and cognitive systems are engaged during the learning of different components of algebraic competence while controlling for demographic and domain general abilities. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Towards a Relation Extraction Framework for Cyber-Security Concepts

    Energy Technology Data Exchange (ETDEWEB)

    Jones, Corinne L [ORNL; Bridges, Robert A [ORNL; Huffer, Kelly M [ORNL; Goodall, John R [ORNL

    2015-01-01

    In order to assist security analysts in obtaining information pertaining to their network, such as novel vulnerabilities, exploits, or patches, information retrieval methods tailored to the security domain are needed. As labeled text data is scarce and expensive, we follow developments in semi-supervised NLP and implement a bootstrapping algorithm for extracting security entities and their relationships from text. The algorithm requires little input data, specifically, a few relations or patterns (heuristics for identifying relations), and incorporates an active learning component which queries the user on the most important decisions to prevent drifting the desired relations. Preliminary testing on a small corpus shows promising results, obtaining precision of .82.

  6. Age of Bilingual Exposure Is Related to the Contribution of Phonological and Semantic Knowledge to Successful Reading Development.

    Science.gov (United States)

    Jasińska, Kaja K; Petitto, Laura-Ann

    2018-01-01

    Bilingual children's reading as a function of age of first bilingual language exposure (AoE) was examined. Bilingual (varied AoE) and monolingual children (N = 421) were compared in their English language and reading abilities (6-10 years) using phonological awareness, semantic knowledge, and reading tasks. Structural equation modeling was applied to determine how bilingual AoE predicts reading outcomes. Early exposed bilinguals outperformed monolinguals on phonological awareness and word reading. Phonology and semantic (vocabulary) knowledge differentially predicted reading depending on the bilingual experience and AoE. Understanding how bilingual experiences impact phonological awareness and semantic knowledge, and in turn, impact reading outcomes is relevant for our understanding of what language and reading skills are best to focus on, and when, to promote optimal reading success. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

  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. The inclusion of biodiversity in environmental impact assessment: Policy-related progress limited by gaps and semantic confusion.

    Science.gov (United States)

    Bigard, Charlotte; Pioch, Sylvain; Thompson, John D

    2017-09-15

    Natural habitat loss and fragmentation, as a result of development projects, are major causes of biodiversity erosion. Environmental impact assessment (EIA) is the most commonly used site-specific planning tool that takes into account the effects of development projects on biodiversity by integrating potential impacts into the mitigation hierarchy of avoidance, reduction, and offset measures. However, the extent to which EIA fully address the identification of impacts and conservation stakes associated with biodiversity loss has been criticized in recent work. In this paper we examine the extent to which biodiversity criteria have been integrated into 42 EIA from 2006 to 2016 for small development projects in the Montpellier Metropolitan territory in southern France. This study system allowed us to question how EIA integrates biodiversity impacts on a scale relevant to land-use planning. We examine how biodiversity inclusion has changed over time in relation to new policy for EIA and how the mitigation hierarchy is implemented in practice and in comparison with national guidelines. We demonstrate that the inclusion of biodiversity features into EIA has increased significantly in relation to policy change. Several weaknesses nevertheless persist, including the continued absence of substitution solution assessment, a correct analysis of cumulative impacts, the evaluation of impacts on common species, the inclusion of an ecological network scale, and the lack of monitoring and evaluation measures. We also show that measures for mitigation hierarchy are primarily associated with the reduction of impacts rather than their avoidance, and avoidance and offset measures are often misleadingly proposed in EIA. There is in fact marked semantic confusion between avoidance, reduction and offset measures that may impair stakeholders' understanding. All in all, reconsideration of stakeholders routine practices associated with a more strategic approach towards impact anticipation

  9. 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’.

  10. CelOWS: an ontology based framework for the provision of semantic web services related to biological models.

    Science.gov (United States)

    Matos, Ely Edison; Campos, Fernanda; Braga, Regina; Palazzi, Daniele

    2010-02-01

    The amount of information generated by biological research has lead to an intensive use of models. Mathematical and computational modeling needs accurate description to share, reuse and simulate models as formulated by original authors. In this paper, we introduce the Cell Component Ontology (CelO), expressed in OWL-DL. This ontology captures both the structure of a cell model and the properties of functional components. We use this ontology in a Web project (CelOWS) to describe, query and compose CellML models, using semantic web services. It aims to improve reuse and composition of existent components and allow semantic validation of new models.

  11. 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…

  12. 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.

  13. Kernel-Based Learning for Domain-Specific Relation Extraction

    Science.gov (United States)

    Basili, Roberto; Giannone, Cristina; Del Vescovo, Chiara; Moschitti, Alessandro; Naggar, Paolo

    In a specific process of business intelligence, i.e. investigation on organized crime, empirical language processing technologies can play a crucial role. The analysis of transcriptions on investigative activities, such as police interrogatories, for the recognition and storage of complex relations among people and locations is a very difficult and time consuming task, ultimately based on pools of experts. We discuss here an inductive relation extraction platform that opens the way to much cheaper and consistent workflows. The presented empirical investigation shows that accurate results, comparable to the expert teams, can be achieved, and parametrization allows to fine tune the system behavior for fitting domain-specific requirements.

  14. Age of Bilingual Exposure Is Related to the Contribution of Phonological and Semantic Knowledge to Successful Reading Development

    Science.gov (United States)

    Jasinska, Kaja K.; Petitto, Laura-Ann

    2018-01-01

    Bilingual children's reading as a function of age of first bilingual language exposure (AoE) was examined. Bilingual (varied AoE) and monolingual children (N = 421) were compared in their English language and reading abilities (6-10 years) using phonological awareness, semantic knowledge, and reading tasks. Structural equation modeling was applied…

  15. Age-Related Differences in Face Recognition: Neural Correlates of Repetition and Semantic Priming in Young and Older Adults

    Science.gov (United States)

    Wiese, Holger; Komes, Jessica; Tüttenberg, Simone; Leidinger, Jana; Schweinberger, Stefan R.

    2017-01-01

    Difficulties in person recognition are among the common complaints associated with cognitive ageing. The present series of experiments therefore investigated face and person recognition in young and older adults. The authors examined how within-domain and cross-domain repetition as well as semantic priming affect familiar face recognition and…

  16. ADEPt, a semantically-enriched pipeline for extracting adverse drug events from free-text electronic health records.

    Directory of Open Access Journals (Sweden)

    Ehtesham Iqbal

    Full Text Available Adverse drug events (ADEs are unintended responses to medical treatment. They can greatly affect a patient's quality of life and present a substantial burden on healthcare. Although Electronic health records (EHRs document a wealth of information relating to ADEs, they are frequently stored in the unstructured or semi-structured free-text narrative requiring Natural Language Processing (NLP techniques to mine the relevant information. Here we present a rule-based ADE detection and classification pipeline built and tested on a large Psychiatric corpus comprising 264k patients using the de-identified EHRs of four UK-based psychiatric hospitals. The pipeline uses characteristics specific to Psychiatric EHRs to guide the annotation process, and distinguishes: a the temporal value associated with the ADE mention (whether it is historical or present, b the categorical value of the ADE (whether it is assertive, hypothetical, retrospective or a general discussion and c the implicit contextual value where the status of the ADE is deduced from surrounding indicators, rather than explicitly stated. We manually created the rulebase in collaboration with clinicians and pharmacists by studying ADE mentions in various types of clinical notes. We evaluated the open-source Adverse Drug Event annotation Pipeline (ADEPt using 19 ADEs specific to antipsychotics and antidepressants medication. The ADEs chosen vary in severity, regularity and persistence. The average F-measure and accuracy achieved by our tool across all tested ADEs were 0.83 and 0.83 respectively. In addition to annotation power, the ADEPT pipeline presents an improvement to the state of the art context-discerning algorithm, ConText.

  17. 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.

  18. 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…

  19. DEXTER: Disease-Expression Relation Extraction from Text.

    Science.gov (United States)

    Gupta, Samir; Dingerdissen, Hayley; Ross, Karen E; Hu, Yu; Wu, Cathy H; Mazumder, Raja; Vijay-Shanker, K

    2018-01-01

    Gene expression levels affect biological processes and play a key role in many diseases. Characterizing expression profiles is useful for clinical research, and diagnostics and prognostics of diseases. There are currently several high-quality databases that capture gene expression information, obtained mostly from large-scale studies, such as microarray and next-generation sequencing technologies, in the context of disease. The scientific literature is another rich source of information on gene expression-disease relationships that not only have been captured from large-scale studies but have also been observed in thousands of small-scale studies. Expression information obtained from literature through manual curation can extend expression databases. While many of the existing databases include information from literature, they are limited by the time-consuming nature of manual curation and have difficulty keeping up with the explosion of publications in the biomedical field. In this work, we describe an automated text-mining tool, Disease-Expression Relation Extraction from Text (DEXTER) to extract information from literature on gene and microRNA expression in the context of disease. One of the motivations in developing DEXTER was to extend the BioXpress database, a cancer-focused gene expression database that includes data derived from large-scale experiments and manual curation of publications. The literature-based portion of BioXpress lags behind significantly compared to expression information obtained from large-scale studies and can benefit from our text-mined results. We have conducted two different evaluations to measure the accuracy of our text-mining tool and achieved average F-scores of 88.51 and 81.81% for the two evaluations, respectively. Also, to demonstrate the ability to extract rich expression information in different disease-related scenarios, we used DEXTER to extract information on differential expression information for 2024 genes in lung

  20. 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.

  1. Extracted facial feature of racial closely related faces

    Science.gov (United States)

    Liewchavalit, Chalothorn; Akiba, Masakazu; Kanno, Tsuneo; Nagao, Tomoharu

    2010-02-01

    Human faces contain a lot of demographic information such as identity, gender, age, race and emotion. Human being can perceive these pieces of information and use it as an important clue in social interaction with other people. Race perception is considered the most delicacy and sensitive parts of face perception. There are many research concerning image-base race recognition, but most of them are focus on major race group such as Caucasoid, Negroid and Mongoloid. This paper focuses on how people classify race of the racial closely related group. As a sample of racial closely related group, we choose Japanese and Thai face to represents difference between Northern and Southern Mongoloid. Three psychological experiment was performed to study the strategies of face perception on race classification. As a result of psychological experiment, it can be suggested that race perception is an ability that can be learn. Eyes and eyebrows are the most attention point and eyes is a significant factor in race perception. The Principal Component Analysis (PCA) was performed to extract facial features of sample race group. Extracted race features of texture and shape were used to synthesize faces. As the result, it can be suggested that racial feature is rely on detailed texture rather than shape feature. This research is a indispensable important fundamental research on the race perception which are essential in the establishment of human-like race recognition system.

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. Semantic Web

    Directory of Open Access Journals (Sweden)

    Anna Lamandini

    2011-06-01

    Full Text Available The semantic Web is a technology at the service of knowledge which is aimed at accessibility and the sharing of content; facilitating interoperability between different systems and as such is one of the nine key technological pillars of TIC (technologies for information and communication within the third theme, programme specific cooperation of the seventh programme framework for research and development (7°PQRS, 2007-2013. As a system it seeks to overcome overload or excess of irrelevant information in Internet, in order to facilitate specific or pertinent research. It is an extension of the existing Web in which the aim is for cooperation between and the computer and people (the dream of Sir Tim Berners –Lee where machines can give more support to people when integrating and elaborating data in order to obtain inferences and a global sharing of data. It is a technology that is able to favour the development of a “data web” in other words the creation of a space in both sets of interconnected and shared data (Linked Data which allows users to link different types of data coming from different sources. It is a technology that will have great effect on everyday life since it will permit the planning of “intelligent applications” in various sectors such as education and training, research, the business world, public information, tourism, health, and e-government. It is an innovative technology that activates a social transformation (socio-semantic Web on a world level since it redefines the cognitive universe of users and enables the sharing not only of information but of significance (collective and connected intelligence.

  7. 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.

  8. Partial sleep deprivation does not alter processes involved in semantic word priming: event-related potential evidence.

    Science.gov (United States)

    Tavakoli, Paniz; Muller-Gass, Alexandra; Campbell, Kenneth

    2015-03-01

    Sleep deprivation has generally been observed to have a detrimental effect on tasks that require sustained attention for successful performance. It might however be possible to counter these effects by altering cognitive strategies. A recent semantic word priming study indicated that subjects used an effortful predictive-expectancy search of semantic memory following normal sleep, but changed to an automatic, effortless strategy following total sleep deprivation. Partial sleep deprivation occurs much more frequently than total sleep deprivation. The present study therefore employed a similar priming task following either 4h of sleep or following normal sleep. The purpose of the study was to determine whether partial sleep deprivation would also lead to a shift in cognitive strategy to compensate for an inability to sustain attention and effortful processing necessary for using the predicative expectancy strategy. Sixteen subjects were presented with word pairs, a prime and a target that were either strongly semantically associated (cat...dog), weakly associated (cow...barn) or not associated (apple...road). The subject's task was to determine if the target word was semantically associated to the prime. A strong priming effect was observed in both conditions. RTs were slower, accuracy lower, and N400 larger to unassociated targets, independent of the amount of sleep. The overall N400 did not differ as a function of sleep. The scalp distribution of the N400 was also similar following both normal sleep and sleep loss. There was thus little evidence of a difference in the processing of the target stimulus as a function of the amount sleep. Similarly, ERPs in the period between the onset of the prime and the subsequent target also did not differ between the normal sleep and sleep loss conditions. In contrast to total sleep deprivation, subjects therefore appeared to use a common predictive expectancy strategy in both conditions. This strategy does however require an

  9. 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

  10. 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.

  11. 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,...

  12. Distant Supervision for Relation Extraction with Ranking-Based Methods

    Directory of Open Access Journals (Sweden)

    Yang Xiang

    2016-05-01

    Full Text Available Relation extraction has benefited from distant supervision in recent years with the development of natural language processing techniques and data explosion. However, distant supervision is still greatly limited by the quality of training data, due to its natural motivation for greatly reducing the heavy cost of data annotation. In this paper, we construct an architecture called MIML-sort (Multi-instance Multi-label Learning with Sorting Strategies, which is built on the famous MIML framework. Based on MIML-sort, we propose three ranking-based methods for sample selection with which we identify relation extractors from a subset of the training data. Experiments are set up on the KBP (Knowledge Base Propagation corpus, one of the benchmark datasets for distant supervision, which is large and noisy. Compared with previous work, the proposed methods produce considerably better results. Furthermore, the three methods together achieve the best F1 on the official testing set, with an optimal enhancement of F1 from 27.3% to 29.98%.

  13. 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...

  14. 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...

  15. 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.

  16. 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.

  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. Method for extracting copper, silver and related metals

    Science.gov (United States)

    Moyer, Bruce A.; McDowell, W. J.

    1990-01-01

    A process for selectively extracting precious metals such as silver and gold concurrent with copper extraction from aqueous solutions containing the same. The process utilizes tetrathiamacrocycles and high molecular weight organic acids that exhibit a synergistic relationship when complexing with certain metal ions thereby removing them from ore leach solutions.

  19. 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

  20. 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.

  1. 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.

  2. 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…

  3. Extracting meronomy relations from domain-specific, textual corporate databases

    NARCIS (Netherlands)

    Ittoo, R.A.; Bouma, G.; Maruster, L.; Wortmann, J.C.; Hopfe, C.J.; Rezgui, Y.; Métais, E.; Preece, A.; Li, H.

    2010-01-01

    Various techniques for learning meronymy relationships from open-domain corpora exist. However, extracting meronymy relationships from domain-specific, textual corporate databases has been overlooked, despite numerous application opportunities particularly in domains like product development and/or

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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…

  11. 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.

  12. Confabulation in healthy aging is related to interference of overlearned, semantically similar information on episodic memory recall.

    Science.gov (United States)

    Dalla Barba, Gianfranco; Attali, Eve; La Corte, Valentina

    2010-07-01

    Normal aging is characterized by reduced performance on tasks of long-term memory. Older adults (OA) not only show reduced performance on tasks of recall and recognition memory, but also, compared to young adults (YA), are more vulnerable to memory distortions. In this study we describe the performance of a group of OA and a group of YA on the recall of three different types of story: a previously unknown story, a well-known fairy tale (Sleeping Beauty), and a modified well-known fairy tale (Little Red Riding Hood is not eaten by the wolf). The aim of our study was to test the hypothesis that in OA strongly represented, overlearned information interferes with episodic recall-that is, the retrieval of specific, unique past episodes. OA produced significantly more confabulations than YA and in particular in the recall of the modified fairy tale. Our findings indicate that the interference of strongly represented, overlearned information in episodic memory recall is implicated in the production of confabulations in OA. This effect is particularly prominent when the to-be remembered episodic information shows strong semantic similarities with preexisting, overlearned information.

  13. 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.

  14. 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...

  15. Ontology-driven extraction of event logs from relational databases

    NARCIS (Netherlands)

    Calvanese, Diego; Montali, Marco; Syamsiyah, Alifah; van der Aalst, Wil M P; Reichert, M.; Reijers, H.A.

    2015-01-01

    Process mining is an emerging discipline whose aim is to discover, monitor and improve real processes by extracting knowledge from event logs representing actual process executions in a given organizational setting. In this light, it can be applied only if faithful event logs, adhering to accepted

  16. 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.

  17. The Effect of Semantic Transparency on the Processing of Morphologically Derived Words: Evidence from Decision Latencies and Event-Related Potentials

    Science.gov (United States)

    Jared, Debra; Jouravlev, Olessia; Joanisse, Marc F.

    2017-01-01

    Decomposition theories of morphological processing in visual word recognition posit an early morpho-orthographic parser that is blind to semantic information, whereas parallel distributed processing (PDP) theories assume that the transparency of orthographic-semantic relationships influences processing from the beginning. To test these…

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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

  4. Pathology report data extraction from relational database using R, with extraction from reports on melanoma of skin as an example.

    Science.gov (United States)

    Ye, Jay J

    2016-01-01

    Different methods have been described for data extraction from pathology reports with varying degrees of success. Here a technique for directly extracting data from relational database is described. Our department uses synoptic reports modified from College of American Pathologists (CAP) Cancer Protocol Templates to report most of our cancer diagnoses. Choosing the melanoma of skin synoptic report as an example, R scripting language extended with RODBC package was used to query the pathology information system database. Reports containing melanoma of skin synoptic report in the past 4 and a half years were retrieved and individual data elements were extracted. Using the retrieved list of the cases, the database was queried a second time to retrieve/extract the lymph node staging information in the subsequent reports from the same patients. 426 synoptic reports corresponding to unique lesions of melanoma of skin were retrieved, and data elements of interest were extracted into an R data frame. The distribution of Breslow depth of melanomas grouped by year is used as an example of intra-report data extraction and analysis. When the new pN staging information was present in the subsequent reports, 82% (77/94) was precisely retrieved (pN0, pN1, pN2 and pN3). Additional 15% (14/94) was retrieved with certain ambiguity (positive or knowing there was an update). The specificity was 100% for both. The relationship between Breslow depth and lymph node status was graphed as an example of lesion-specific multi-report data extraction and analysis. R extended with RODBC package is a simple and versatile approach well-suited for the above tasks. The success or failure of the retrieval and extraction depended largely on whether the reports were formatted and whether the contents of the elements were consistently phrased. This approach can be easily modified and adopted for other pathology information systems that use relational database for data management.

  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. 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...

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. Polish Semantic Parser

    Directory of Open Access Journals (Sweden)

    Agnieszka Grudzinska

    2000-01-01

    Full Text Available Amount of information transferred by computers grows very rapidly thus outgrowing the average man's capability of reception. It implies computer programs increase in the demand for which would be able to perform an introductory classitication or even selection of information directed to a particular receiver. Due to the complexity of the problem, we restricted it to understanding short newspaper notes. Among many conceptions formulated so far, the conceptual dependency worked out by Roger Schank has been chosen. It is a formal language of description of the semantics of pronouncement integrated with a text understanding algorithm. Substantial part of each text transformation system is a semantic parser of the Polish language. It is a module, which as the first and the only one has an access to the text in the Polish language. lt plays the role of an element, which finds relations between words of the Polish language and the formal registration. It translates sentences written in the language used by people into the language theory. The presented structure of knowledge units and the shape of understanding process algorithms are universal by virtue of the theory. On the other hand the defined knowledge units and the rules used in the algorithms ure only examples because they are constructed in order to understand short newspaper notes.

  13. Semantics and pragmatics.

    Science.gov (United States)

    McNally, Louise

    2013-05-01

    The fields of semantics and pragmatics are devoted to the study of conventionalized and context- or use-dependent aspects of natural language meaning, respectively. The complexity of human language as a semiotic system has led to considerable debate about how the semantics/pragmatics distinction should be drawn, if at all. This debate largely reflects contrasting views of meaning as a property of linguistic expressions versus something that speakers do. The fact that both views of meaning are essential to a complete understanding of language has led to a variety of efforts over the last 40 years to develop better integrated and more comprehensive theories of language use and interpretation. The most important advances have included the adaptation of propositional analyses of declarative sentences to interrogative, imperative and exclamative forms; the emergence of dynamic, game theoretic, and multi-dimensional theories of meaning; and the development of various techniques for incorporating context-dependent aspects of content into representations of context-invariant content with the goal of handling phenomena such as vagueness resolution, metaphor, and metonymy. WIREs Cogn Sci 2013, 4:285-297. doi: 10.1002/wcs.1227 For further resources related to this article, please visit the WIREs website. The authors declare no conflict of interest. Copyright © 2013 John Wiley & Sons, Ltd.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. Metamodeling of Semantic Web Enabled Multiagent Systems

    NARCIS (Netherlands)

    Kardas, G.; Göknil, Arda; Dikenelli, O.; Topaloglu, N.Y.; Weyns, D.; Holvoet, T.

    2006-01-01

    Several agent researchers are currently studying agent modeling and they propose dierent architectural metamodels for developing Multiagent Systems (MAS) according to specic agent development methodologies. When support for Semantic Web technology and its related constructs are considered, agent

  19. 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...

  20. Dental extractions in relation to radiation therapy of 224 patients

    International Nuclear Information System (INIS)

    Makkonen, T.A.; Kiminki, A.; Makkonen, T.K.; Nordman, E.

    1987-01-01

    The case histories of 224 patients treated with radiation therapy for head and neck malignancies at the Radiotherapy Clinic of the Univesity Central Hospital in Turku during the years 1974-77 are reviewed. Of the 92 patients surviving for 5 years, 90 were available for re-examination. The median radiation dosage was 61 Gy in 6 to 8 weeks in patients with squamous cell carcinoma and othe solid tumours and 43 Gy in 5 weeks in patients with lymphoma. The oral status of the patients was examined clinically and radiographically. From these pationts 45 teeth had been extracted before irradiation and 94 after irradiation. In no case had this resulted in osteoradionecrosis of the jaws. It is evident that the repairing of patient's teeth before radiation treatment, coupled with continuous preventive care of caries, will prevent serious complications from arising. (author)

  1. 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.

  2. 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

  3. 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

  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. 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.

  6. 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

  7. 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

  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 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...

  10. EXTRACTING TOPOLOGICAL RELATIONS BETWEEN INDOOR SPACES FROM POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    H. Tran

    2017-09-01

    Full Text Available 3D models of indoor environments are essential for many application domains such as navigation guidance, emergency management and a range of indoor location-based services. The principal components defined in different BIM standards contain not only building elements, such as floors, walls and doors, but also navigable spaces and their topological relations, which are essential for path planning and navigation. We present an approach to automatically reconstruct topological relations between navigable spaces from point clouds. Three types of topological relations, namely containment, adjacency and connectivity of the spaces are modelled. The results of initial experiments demonstrate the potential of the method in supporting indoor navigation.

  11. Pathology report data extraction from relational database using R, with extraction from reports on melanoma of skin as an example

    Directory of Open Access Journals (Sweden)

    Jay J Ye

    2016-01-01

    Full Text Available Background: Different methods have been described for data extraction from pathology reports with varying degrees of success. Here a technique for directly extracting data from relational database is described. Methods: Our department uses synoptic reports modified from College of American Pathologists (CAP Cancer Protocol Templates to report most of our cancer diagnoses. Choosing the melanoma of skin synoptic report as an example, R scripting language extended with RODBC package was used to query the pathology information system database. Reports containing melanoma of skin synoptic report in the past 4 and a half years were retrieved and individual data elements were extracted. Using the retrieved list of the cases, the database was queried a second time to retrieve/extract the lymph node staging information in the subsequent reports from the same patients. Results: 426 synoptic reports corresponding to unique lesions of melanoma of skin were retrieved, and data elements of interest were extracted into an R data frame. The distribution of Breslow depth of melanomas grouped by year is used as an example of intra-report data extraction and analysis. When the new pN staging information was present in the subsequent reports, 82% (77/94 was precisely retrieved (pN0, pN1, pN2 and pN3. Additional 15% (14/94 was retrieved with certain ambiguity (positive or knowing there was an update. The specificity was 100% for both. The relationship between Breslow depth and lymph node status was graphed as an example of lesion-specific multi-report data extraction and analysis. Conclusions: R extended with RODBC package is a simple and versatile approach well-suited for the above tasks. The success or failure of the retrieval and extraction depended largely on whether the reports were formatted and whether the contents of the elements were consistently phrased. This approach can be easily modified and adopted for other pathology information systems that use

  12. A Formal Framework on the Semantics of Regulatory Relations and Their Presence as Verbs in Biomedical Texts

    DEFF Research Database (Denmark)

    Zambach, Sine

    2009-01-01

    Relations used in biomedical ontologies and expressed in biomedical texts can be very general or very specific. Regulatory relations are used widely in regulatory networks, for example, and therefore they appear systematically and highly frequently in biomedical texts. This work focuses on the lo......Relations used in biomedical ontologies and expressed in biomedical texts can be very general or very specific. Regulatory relations are used widely in regulatory networks, for example, and therefore they appear systematically and highly frequently in biomedical texts. This work focuses...

  13. 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...

  14. 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

  15. 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...

  16. 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.

  17. 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.

  18. EXTRACT

    DEFF Research Database (Denmark)

    Pafilis, Evangelos; Buttigieg, Pier Luigi; Ferrell, Barbra

    2016-01-01

    The microbial and molecular ecology research communities have made substantial progress on developing standards for annotating samples with environment metadata. However, sample manual annotation is a highly labor intensive process and requires familiarity with the terminologies used. We have the...... and text-mining-assisted curation revealed that EXTRACT speeds up annotation by 15-25% and helps curators to detect terms that would otherwise have been missed.Database URL: https://extract.hcmr.gr/......., organism, tissue and disease terms. The evaluators in the BioCreative V Interactive Annotation Task found the system to be intuitive, useful, well documented and sufficiently accurate to be helpful in spotting relevant text passages and extracting organism and environment terms. Comparison of fully manual...

  19. 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

  20. Semantic Business Process Modeling

    OpenAIRE

    Markovic, Ivan

    2010-01-01

    This book presents a process-oriented business modeling framework based on semantic technologies. The framework consists of modeling languages, methods, and tools that allow for semantic modeling of business motivation, business policies and rules, and business processes. Quality of the proposed modeling framework is evaluated based on the modeling content of SAP Solution Composer and several real-world business scenarios.

  1. 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

  2. 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...

  3. 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

  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. 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.

  6. 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

  7. 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.

  8. Extraction of Children's Friendship Relation from Activity Level

    Science.gov (United States)

    Kono, Aki; Shintani, Kimio; Katsuki, Takuya; Kihara, Shin'ya; Ueda, Mari; Kaneda, Shigeo; Haga, Hirohide

    Children learn to fit into society through living in a group, and it's greatly influenced by their friend relations. Although preschool teachers need to observe them to assist in the growth of children's social progress and support the development each child's personality, only experienced teachers can watch over children while providing high-quality guidance. To resolve the problem, this paper proposes a mathematical and objective method that assists teachers with observation. It uses numerical data of activity level recorded by pedometers, and we make tree diagram called dendrogram based on hierarchical clustering with recorded activity level. Also, we calculate children's ``breadth'' and ``depth'' of friend relations by using more than one dendrogram. When we record children's activity level in a certain kindergarten for two months and evaluated the proposed method, the results usually coincide with remarks of teachers about the children.

  9. Quantitative Structure-Relative Volatility Relationship Model for Extractive Distillation of Ethylbenzene/p-Xylene Mixtures: Application to Binary and Ternary Mixtures as Extractive Agents

    International Nuclear Information System (INIS)

    Kang, Young-Mook; Oh, Kyunghwan; You, Hwan; No, Kyoung Tai; Jeon, Yukwon; Shul, Yong-Gun; Hwang, Sung Bo; Shin, Hyun Kil; Kim, Min Sung; Kim, Namseok; Son, Hyoungjun; Chu, Young Hwan; Cho, Kwang-Hwi

    2016-01-01

    Ethylbenzene (EB) and p-xylene (PX) are important chemicals for the production of industrial materials; accordingly, their efficient separation is desired, even though the difference in their boiling points is very small. This paper describes the efforts toward the identification of high-performance extractive agents for EB and PX separation by distillation. Most high-performance extractive agents contain halogen atoms, which present health hazards and are corrosive to distillation plates. To avoid this disadvantage of extractive agents, we developed a quantitative structure-relative volatility relationship (QSRVR) model for designing safe extractive agents. We have previously developed and reported QSRVR models for single extractive agents. In this study, we introduce extended QSRVR models for binary and ternary extractive agents. The QSRVR models accurately predict the relative volatilities of binary and ternary extractive agents. The service to predict the relative volatility for binary and ternary extractive agents is freely available from the Internet at http://qsrvr.o pengsi.org/.

  10. Quantitative Structure-Relative Volatility Relationship Model for Extractive Distillation of Ethylbenzene/p-Xylene Mixtures: Application to Binary and Ternary Mixtures as Extractive Agents

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Young-Mook; Oh, Kyunghwan; You, Hwan; No, Kyoung Tai [Bioinformatics and Molecular Design Research Center, Seoul (Korea, Republic of); Jeon, Yukwon; Shul, Yong-Gun; Hwang, Sung Bo; Shin, Hyun Kil; Kim, Min Sung; Kim, Namseok; Son, Hyoungjun [Yonsei University, Seoul (Korea, Republic of); Chu, Young Hwan [Sangji University, Wonju (Korea, Republic of); Cho, Kwang-Hwi [Soongsil University, Seoul (Korea, Republic of)

    2016-04-15

    Ethylbenzene (EB) and p-xylene (PX) are important chemicals for the production of industrial materials; accordingly, their efficient separation is desired, even though the difference in their boiling points is very small. This paper describes the efforts toward the identification of high-performance extractive agents for EB and PX separation by distillation. Most high-performance extractive agents contain halogen atoms, which present health hazards and are corrosive to distillation plates. To avoid this disadvantage of extractive agents, we developed a quantitative structure-relative volatility relationship (QSRVR) model for designing safe extractive agents. We have previously developed and reported QSRVR models for single extractive agents. In this study, we introduce extended QSRVR models for binary and ternary extractive agents. The QSRVR models accurately predict the relative volatilities of binary and ternary extractive agents. The service to predict the relative volatility for binary and ternary extractive agents is freely available from the Internet at http://qsrvr.o pengsi.org/.

  11. 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...

  12. 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...

  13. Event-related potentials and oscillatory brain responses associated with semantic and Stroop-like interference effects in overt naming

    NARCIS (Netherlands)

    Piai, V.; Roelofs, A.P.A.; Meij, R. van der

    2012-01-01

    Picture–word interference is a widely employed paradigm to investigate lexical access in word production: Speakers name pictures while trying to ignore superimposed distractor words. The distractor can be congruent to the picture (pictured cat, word cat), categorically related (pictured cat, word

  14. 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....

  15. Semantic Madurese Batik Search with Cultural Computing of Symbolic Impression Extraction and Analytical Aggregation of Color,Shape and Area Features

    Directory of Open Access Journals (Sweden)

    Khotibul Umam

    2017-07-01

    Full Text Available Lack of information media about Madurese batik Causes low awareness of younger generation to maintain the production of Madurese batik. Actually, Madurese Batik also has a high philosophy, which the motif and colour reflect the character of the Madurese. Madurese Batik has useful motif as a mean of traditional communication in the form of certain cultural symbols. We collected images of Madurese Batik by identifying the impression of Madurese Batik motif taken from several literature books of Madurese Batik and also the results of observation of experts or craftsmen who understand about Madurese Batik. This research proposed a new approach to create on application which can identify Madurese Batik impression by using 3D-CVQ feature extraction methods to extract color features, and used Hu Moment Invariant for feature feature extraction. Application searching of Madurese Batik image has two ways of searching, those are based on the image input Madurese Batik and based on the input of impression Madurese batik. We use 202 madurese batik motifs and use search techniques based on colors, shapes and aggregations (color and shape combinations.  Performance results using based on image queries used: (1 based on color, the average precision 90%, (2 based on shape, the average precision 85%, (3 based on aggregation, the average precision 80%, the conclusion is the color as the best feature in image query. While the performance results using based on the impression query are:  (1 based on color, the average value of true 6.7, total score 40.3, (2 based on shape, the average value of true 4.1, total score 24.1, and (3 based on the aggregation, the average value of true 2.5, the total score is 13.8, the conclusion is the color as the best feature in impression query.

  16. A database for extract solutions in general relativity

    International Nuclear Information System (INIS)

    Horvath, I.; Horvath, Zs.; Lukacs, B.

    1993-07-01

    The field of equations of General Relativity are coupled second order partial differential equations. Therefore no general method is known to generate solutions for prescribed initial and boundary conditions. In addition, the meaning of the particular coordinates cannot be known until the metric is not found. Therefore the result must permit arbitrary coordinate transformations, i.e. most kinds of approximating methods are improper. So exact solutions are necessary and each one is an individual product. For storage, retrieval and comparison database handling techniques are needed. A database of 1359 articles is shown (cross-referred at least once) published in 156 more important journals. It can be handled by dBase III plus on IBM PC's. (author) 5 refs.; 5 tabs

  17. An unsupervised text mining method for relation extraction from biomedical literature.

    Directory of Open Access Journals (Sweden)

    Changqin Quan

    Full Text Available The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs. Dependency parsing and phrase structure parsing are combined for relation extraction. Based on the semi-supervised KNN algorithm, we extend the proposed unsupervised approach to a semi-supervised approach by combining pattern clustering, dependency parsing and phrase structure parsing rules. We evaluated the approaches on two different tasks: (1 Protein-protein interactions extraction, and (2 Gene-suicide association extraction. The evaluation of task (1 on the benchmark dataset (AImed corpus showed that our proposed unsupervised approach outperformed three supervised methods. The three supervised methods are rule based, SVM based, and Kernel based separately. The proposed semi-supervised approach is superior to the existing semi-supervised methods. The evaluation on gene-suicide association extraction on a smaller dataset from Genetic Association Database and a larger dataset from publicly available PubMed showed that the proposed unsupervised and semi-supervised methods achieved much higher F-scores than co-occurrence based method.

  18. 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.

  19. THE TERMS OF INHERITANCE LAW IN RUSSIA-BYZANTIUM TREATIES AND RUSSKAYA PRAVDA: THE PROBLEMS OF FUNCTIONAL SEMANTICS AND DERIVATION RELATIONS

    Directory of Open Access Journals (Sweden)

    Kirzhaeva Vera Petrovna

    2014-12-01

    Full Text Available The article deals with the functional-and-semantic and derivational relations of the inheritance law terms in the Russia-Byzantium treaties and in Russkaya Pravda Legal Code as well as in the wide-spread Church Slavonic law regulators that appeared in Rus after adoption of Christianity. The research results attest that the inheritance law terminology in treaties includes designation of inheritance, will and heirs. There is a special term chast ('part' that denotes a share of inheritance in the Russkaya Pravda and Church Slavonic legal texts. However, chast as a 'part' (share is a characteristic of the Russkaya Pravda legal texts only. In Church Slavonic it is used in treaties for nominating the property in general. A similar lack of strict distribution between inheritance law terms zadnitsa and dom, presented in Old Russian texts, was noted in Church Slavonic treaties. Various derivatives of the root *rÌd- are used to denote the will in all texts under analysis; the terms pisati employed only in treaties and church law regulators to denote a written will or procedures of its preparation. The derivatives of the root *bliz- nominate the heirs in both text systems. A loan translation of the terminological word group malye / milye blizhnie / blizhiki dated to the year 911 is not viewed as a translators' experiment with the Greek terms, because it reflects a steady lexical distribution of adjectives malye / milye and the terms of relations in the Russian language. The results of the study testify some inheritance law terms correlation between Russia-Byzantium treaties, Russkaya Pravda and Church Slavonic legal texts, their translation in the treaties was not entirely artificial. The Church Slavonic and Old Russian terminological systems were open to these interferences in some ways.

  20. Is the use of Gunnera perpensa extracts in endometritis related to antibacterial activ

    Directory of Open Access Journals (Sweden)

    L.J. McGaw

    2005-09-01

    Full Text Available Rhizome extracts of Gunnera perpensa are used in traditional remedies in South Africa to treat endometritis both in humans and animals. An investigation was undertaken to determine whether this plant possesses antibacterial activity, which may explain its efficacy. Gunnera perpensa rhizome extracts were prepared serially with solvents of increasing polarity and tested for antibacterial activity. Test bacteria included the Gram-positive Enterococcus faecalis and Staphylococcus aureus and the Gram-negative Escherichia coli and Pseudomonas aeruginosa. A moderate to weak level of antibacterial activity in most of the extracts resulted, with the best minimal inhibitory concentration (MIC value of 2.61 mg ml-1 shown by the acetone extract against S. aureus. The extracts were also submitted to the brine shrimp assay to detect possible toxic or pharmacological effects. All the extracts were lethal to the brine shrimp larvae at a concentration of 5 mg ml-1. The acetone extract was extremely toxic at 1 mg ml-1, with some toxicity evident at 0.1 mg ml-1. The remainder of the extracts generally displayed little activity at concentrations lower than 5 mg ml-1. In summary, the results indicate that although the extracts demonstrated a level of pharmacological activity, the relatively weak antibacterial activity is unlikely to justify the use of G. perpensa rhizomes in the traditional treatment of endometritis. Rather, the slightly antibacterial nature of the rhizomes may contribute to an additive effect, along with their known uterotonic activity, to the overall efficacy of the preparation.

  1. 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.

  2. 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.

  3. 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…

  4. 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.

  5. 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:

  6. 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

  7. 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...

  8. 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 ...

  9. 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

  10. Complications of Translating the Meanings of the Holy Qur'an at Word Level in the English Language in Relation to Frame Semantic Theory

    Science.gov (United States)

    Balla, Asjad Ahmed Saeed; Siddiek, Ahmed Gumaa

    2017-01-01

    The present study is an attempt to investigate the problems resulting from the lexical choice in the translation of the Holy Qur'an to emphasize the importance of the theory of "Frame Semantics" in the translation process. It has been conducted with the aim of measuring the difference in concept between the two languages Arabic and…

  11. 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. ...

  12. Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning

    Directory of Open Access Journals (Sweden)

    Yuntian Feng

    2017-01-01

    Full Text Available We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically capture the most important information from unstructured texts, which represent the state in the decision process. By designing the reward function per step, our proposed method can pass the information of entity extraction to relation extraction and obtain feedback in order to extract entities and relations simultaneously. Firstly, we use bidirectional LSTM to model the context information, which realizes preliminary entity extraction. On the basis of the extraction results, attention based method can represent the sentences that include target entity pair to generate the initial state in the decision process. Then we use Tree-LSTM to represent relation mentions to generate the transition state in the decision process. Finally, we employ Q-Learning algorithm to get control policy π in the two-step decision process. Experiments on ACE2005 demonstrate that our method attains better performance than the state-of-the-art method and gets a 2.4% increase in recall-score.

  13. Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning.

    Science.gov (United States)

    Feng, Yuntian; Zhang, Hongjun; Hao, Wenning; Chen, Gang

    2017-01-01

    We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically capture the most important information from unstructured texts, which represent the state in the decision process. By designing the reward function per step, our proposed method can pass the information of entity extraction to relation extraction and obtain feedback in order to extract entities and relations simultaneously. Firstly, we use bidirectional LSTM to model the context information, which realizes preliminary entity extraction. On the basis of the extraction results, attention based method can represent the sentences that include target entity pair to generate the initial state in the decision process. Then we use Tree-LSTM to represent relation mentions to generate the transition state in the decision process. Finally, we employ Q -Learning algorithm to get control policy π in the two-step decision process. Experiments on ACE2005 demonstrate that our method attains better performance than the state-of-the-art method and gets a 2.4% increase in recall-score.

  14. PKDE4J: Entity and relation extraction for public knowledge discovery.

    Science.gov (United States)

    Song, Min; Kim, Won Chul; Lee, Dahee; Heo, Go Eun; Kang, Keun Young

    2015-10-01

    Due to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical field. Such techniques provide effective means of information search, knowledge discovery, and hypothesis generation. Most previous studies have primarily focused on the design and performance improvement of either named entity recognition or relation extraction. In this paper, we present PKDE4J, a comprehensive text-mining system that integrates dictionary-based entity extraction and rule-based relation extraction in a highly flexible and extensible framework. Starting with the Stanford CoreNLP, we developed the system to cope with multiple types of entities and relations. The system also has fairly good performance in terms of accuracy as well as the ability to configure text-processing components. We demonstrate its competitive performance by evaluating it on many corpora and found that it surpasses existing systems with average F-measures of 85% for entity extraction and 81% for relation extraction. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Algebraic Semantics for Narrative

    Science.gov (United States)

    Kahn, E.

    1974-01-01

    This paper uses discussion of Edmund Spenser's "The Faerie Queene" to present a theoretical framework for explaining the semantics of narrative discourse. The algebraic theory of finite automata is used. (CK)

  16. Semantic Web Development

    National Research Council Canada - National Science Library

    Berners-Lee, Tim; Swick, Ralph

    2006-01-01

    ...) project between 2002 and 2005 provided key steps in the research in the Semantic Web technology, and also played an essential role in delivering the technology to industry and government in the form...

  17. 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.

  18. 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

  19. Extracting relations from traditional Chinese medicine literature via heterogeneous entity networks.

    Science.gov (United States)

    Wan, Huaiyu; Moens, Marie-Francine; Luyten, Walter; Zhou, Xuezhong; Mei, Qiaozhu; Liu, Lu; Tang, Jie

    2016-03-01

    Traditional Chinese medicine (TCM) is a unique and complex medical system that has developed over thousands of years. This article studies the problem of automatically extracting meaningful relations of entities from TCM literature, for the purposes of assisting clinical treatment or poly-pharmacology research and promoting the understanding of TCM in Western countries. Instead of separately extracting each relation from a single sentence or document, we propose to collectively and globally extract multiple types of relations (eg, herb-syndrome, herb-disease, formula-syndrome, formula-disease, and syndrome-disease relations) from the entire corpus of TCM literature, from the perspective of network mining. In our analysis, we first constructed heterogeneous entity networks from the TCM literature, in which each edge is a candidate relation, then used a heterogeneous factor graph model (HFGM) to simultaneously infer the existence of all the edges. We also employed a semi-supervised learning algorithm estimate the model's parameters. We performed our method to extract relations from a large dataset consisting of more than 100,000 TCM article abstracts. Our results show that the performance of the HFGM at extracting all types of relations from TCM literature was significantly better than a traditional support vector machine (SVM) classifier (increasing the average precision by 11.09%, the recall by 13.83%, and the F1-measure by 12.47% for different types of relations, compared with a traditional SVM classifier). This study exploits the power of collective inference and proposes an HFGM based on heterogeneous entity networks, which significantly improved our ability to extract relations from TCM literature. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  20. Characteristics of prickly lettuce seed oil in relation to methods of extraction.

    Science.gov (United States)

    Ramadan, A A

    1976-01-01

    Samples of seed oil of prickly lettuce (Lactuca Sacriola oleifera) which had been obtained by pressing or by extracting with acetone, ethyl ether, petroleum ether or carbon tetrachloride were analysed for the following parameters: viscosity, saponification number, iodine number, thiocyanogen value, unsaponifiable matter, free fatty acids, peroxide number and fatty acid composition. The different parameters varied in part considerably in relation to the method of production (pressing or solvent extraction) and to the solvent. It is tried to interprete these relationships.

  1. 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.

  2. 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...

  3. Zero drift and solid Earth tide extracted from relative gravimetric data with principal component analysis

    OpenAIRE

    Hongjuan Yu; Jinyun Guo; Jiulong Li; Dapeng Mu; Qiaoli Kong

    2015-01-01

    Zero drift and solid Earth tide corrections to static relative gravimetric data cannot be ignored. In this paper, a new principal component analysis (PCA) algorithm is presented to extract the zero drift and the solid Earth tide, as signals, from static relative gravimetric data assuming that the components contained in the relative gravimetric data are uncorrelated. Static relative gravity observations from Aug. 15 to Aug. 23, 2014 are used as statistical variables to separate the signal and...

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. Relation between Silver Nanoparticle Formation Rate and Antioxidant Capacity of Aqueous Plant Leaf Extracts

    Directory of Open Access Journals (Sweden)

    Azat Akbal

    2016-01-01

    Full Text Available Correlation between the antioxidant capacity and silver nanoparticle formation rates of pomegranate (Punica granatum, quince (Cydonia oblonga, chestnut (Castanea sativa, fig (Ficus carica, walnut (Juglans cinerea, black mulberry (Morus nigra, and white mulberry (Morus alba leaf extracts is investigated at a fixed illumination. Silver nanoparticles formed in all plant leaf extracts possess round shapes with average particle size of 15 to 25 nm, whereas corresponding surface plasmon resonance peak wavelengths vary between 422 nm and 451 nm. Cupric reducing antioxidant capacity technique is used as a reference method to determine total antioxidant capacity of the plant leaf extracts. Integrated absorbance over the plasmon resonance peaks exhibits better linear relation with antioxidant capacities of various plant leaf extracts compared to peak absorbance values, with correlation coefficient values of 0.9333 and 0.7221, respectively.

  9. 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

  10. 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.

  11. 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

  12. 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...

  13. 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%.

  14. Detailed semantic analyses of human error incidents occurring at nuclear power plants. Extraction of periodical transition of error occurrence patterns by applying multivariate analysis

    International Nuclear Information System (INIS)

    Hirotsu, Yuko; Suzuki, Kunihiko; Takano, Kenichi; Kojima, Mitsuhiro

    2000-01-01

    It is essential for preventing the recurrence of human error incidents to analyze and evaluate them with the emphasis on human factor. Detailed and structured analyses of all incidents at domestic nuclear power plants (NPPs) reported during last 31 years have been conducted based on J-HPES, in which total 193 human error cases are identified. Results obtained by the analyses have been stored into the J-HPES database. In the previous study, by applying multivariate analysis to above case studies, it was suggested that there were several occurrence patterns identified of how errors occur at NPPs. It was also clarified that the causes related to each human error are different depending on age of their occurrence. This paper described the obtained results in respects of periodical transition of human error occurrence patterns. By applying multivariate analysis to the above data, it was suggested there were two types of error occurrence patterns as to each human error type. First type is common occurrence patterns, not depending on the age, and second type is the one influenced by periodical characteristics. (author)

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. MeInfoText 2.0: gene methylation and cancer relation extraction from biomedical literature

    Directory of Open Access Journals (Sweden)

    Fang Yu-Ching

    2011-12-01

    Full Text Available Abstract Background DNA methylation is regarded as a potential biomarker in the diagnosis and treatment of cancer. The relations between aberrant gene methylation and cancer development have been identified by a number of recent scientific studies. In a previous work, we used co-occurrences to mine those associations and compiled the MeInfoText 1.0 database. To reduce the amount of manual curation and improve the accuracy of relation extraction, we have now developed MeInfoText 2.0, which uses a machine learning-based approach to extract gene methylation-cancer relations. Description Two maximum entropy models are trained to predict if aberrant gene methylation is related to any type of cancer mentioned in the literature. After evaluation based on 10-fold cross-validation, the average precision/recall rates of the two models are 94.7/90.1 and 91.8/90% respectively. MeInfoText 2.0 provides the gene methylation profiles of different types of human cancer. The extracted relations with maximum probability, evidence sentences, and specific gene information are also retrievable. The database is available at http://bws.iis.sinica.edu.tw:8081/MeInfoText2/. Conclusion The previous version, MeInfoText, was developed by using association rules, whereas MeInfoText 2.0 is based on a new framework that combines machine learning, dictionary lookup and pattern matching for epigenetics information extraction. The results of experiments show that MeInfoText 2.0 outperforms existing tools in many respects. To the best of our knowledge, this is the first study that uses a hybrid approach to extract gene methylation-cancer relations. It is also the first attempt to develop a gene methylation and cancer relation corpus.

  1. Design of the Injection and extraction system and related machine protection for the Clic Damping Rings

    CERN Document Server

    Apsimon, Robert; Barnes, Mike; Borburgh, Jan; Goddard, Brennan; Papaphilippou, Yannis; Uythoven, Jan

    2014-01-01

    Linear machines such as CLIC have relatively low rates of collision between bunches compared to their circular counterparts. In order to achieve the required luminosity, a very small spot size is envisaged at the interaction point, thus a low emittance beam is needed. Damping rings are essential for producing the low emittances needed for the CLIC main beam. It is crucial that the beams are injected and extracted from the damping rings in a stable and repeatable fashion to minimise emittance blow-up and beam jitter at the interaction point; both of these effects will deteriorate the luminosity at the interaction point. In this paper, the parameters and constraints of the injection and extraction systems are considered and the design of these systems is optimised within this parameter space. Related machine protection is considered in order to prevent damage from potential failure modes of the injection and extraction systems.

  2. 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,…

  3. Semantic Learning Service Personalized

    Directory of Open Access Journals (Sweden)

    Yibo Chen

    2012-02-01

    Full Text Available To provide users with more suitable and personalized service, personalization is widely used in various fields. Current e-Learning systems search for learning resources using information search technology, based on the keywords that selected or inputted by the user. Due to lack of semantic analysis for keywords and exploring the user contexts, the system cannot provide a good learning experiment. In this paper, we defined the concept and characteristic of the personalized learning service, and proposed a semantic learning service personalized framework. Moreover, we made full use of semantic technology, using ontologies to represent the learning contents and user profile, mining and utilizing the friendship and membership of the social relationship to construct the user social relationship profile, and improved the collaboration filtering algorithm to recommend personalized learning resources for users. The results of the empirical evaluation show that the approach is effectiveness in augmenting recommendation.

  4. Semantic Observation Integration

    Directory of Open Access Journals (Sweden)

    Werner Kuhn

    2012-09-01

    Full Text Available Although the integration of sensor-based information into analysis and decision making has been a research topic for many years, semantic interoperability has not yet been reached. The advent of user-generated content for the geospatial domain, Volunteered Geographic Information (VGI, makes it even more difficult to establish semantic integration. This paper proposes a novel approach to integrating conventional sensor information and VGI, which is exploited in the context of detecting forest fires. In contrast to common logic-based semantic descriptions, we present a formal system using algebraic specifications to unambiguously describe the processing steps from natural phenomena to value-added information. A generic ontology of observations is extended and profiled for forest fire detection in order to illustrate how the sensing process, and transformations between heterogeneous sensing systems, can be represented as mathematical functions and grouped into abstract data types. We discuss the required ontological commitments and a possible generalization.

  5. 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

  6. 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.

  7. 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...

  8. 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)....

  9. Extracting microRNA-gene relations from biomedical literature using distant supervision.

    Directory of Open Access Journals (Sweden)

    Andre Lamurias

    Full Text Available Many biomedical relation extraction approaches are based on supervised machine learning, requiring an annotated corpus. Distant supervision aims at training a classifier by combining a knowledge base with a corpus, reducing the amount of manual effort necessary. This is particularly useful for biomedicine because many databases and ontologies have been made available for many biological processes, while the availability of annotated corpora is still limited. We studied the extraction of microRNA-gene relations from text. MicroRNA regulation is an important biological process due to its close association with human diseases. The proposed method, IBRel, is based on distantly supervised multi-instance learning. We evaluated IBRel on three datasets, and the results were compared with a co-occurrence approach as well as a supervised machine learning algorithm. While supervised learning outperformed on two of those datasets, IBRel obtained an F-score 28.3 percentage points higher on the dataset for which there was no training set developed specifically. To demonstrate the applicability of IBRel, we used it to extract 27 miRNA-gene relations from recently published papers about cystic fibrosis. Our results demonstrate that our method can be successfully used to extract relations from literature about a biological process without an annotated corpus. The source code and data used in this study are available at https://github.com/AndreLamurias/IBRel.

  10. Evolution of semantic systems

    CERN Document Server

    Küppers, Bernd-Olaf; Artmann, Stefan

    2013-01-01

    Complex systems in nature and society make use of information for the development of their internal organization and the control of their functional mechanisms. Alongside technical aspects of storing, transmitting and processing information, the various semantic aspects of information, such as meaning, sense, reference and function, play a decisive part in the analysis of such systems.With the aim of fostering a better understanding of semantic systems from an evolutionary and multidisciplinary perspective, this volume collects contributions by philosophers and natural scientists, linguists, i

  11. 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…

  12. 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.

  13. A method for automatically extracting infectious disease-related primers and probes from the literature

    Directory of Open Access Journals (Sweden)

    Pérez-Rey David

    2010-08-01

    Full Text Available Abstract Background Primer and probe sequences are the main components of nucleic acid-based detection systems. Biologists use primers and probes for different tasks, some related to the diagnosis and prescription of infectious diseases. The biological literature is the main information source for empirically validated primer and probe sequences. Therefore, it is becoming increasingly important for researchers to navigate this important information. In this paper, we present a four-phase method for extracting and annotating primer/probe sequences from the literature. These phases are: (1 convert each document into a tree of paper sections, (2 detect the candidate sequences using a set of finite state machine-based recognizers, (3 refine problem sequences using a rule-based expert system, and (4 annotate the extracted sequences with their related organism/gene information. Results We tested our approach using a test set composed of 297 manuscripts. The extracted sequences and their organism/gene annotations were manually evaluated by a panel of molecular biologists. The results of the evaluation show that our approach is suitable for automatically extracting DNA sequences, achieving precision/recall rates of 97.98% and 95.77%, respectively. In addition, 76.66% of the detected sequences were correctly annotated with their organism name. The system also provided correct gene-related information for 46.18% of the sequences assigned a correct organism name. Conclusions We believe that the proposed method can facilitate routine tasks for biomedical researchers using molecular methods to diagnose and prescribe different infectious diseases. In addition, the proposed method can be expanded to detect and extract other biological sequences from the literature. The extracted information can also be used to readily update available primer/probe databases or to create new databases from scratch.

  14. 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…

  15. [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.

  16. Semantic Barbs and Biorthogonality

    OpenAIRE

    Rathke, J.; Sassone, V.; Sobocinski, P.

    2007-01-01

    We use the framework of biorthogonality to introduce a novel semantic definition of the concept of barb (basic observable) for process calculi. We develop a uniform basic theory of barbs and demonstrate its robustness by showing that it gives rise to the correct observables in specific process calculi which model synchronous, asynchronous and broadcast communication regimes.

  17. The semantic similarity ensemble

    Directory of Open Access Journals (Sweden)

    Andrea Ballatore

    2013-12-01

    Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

  18. Learning semantic query suggestions

    NARCIS (Netherlands)

    Meij, E.; Bron, M.; Hollink, L.; Huurnink, B.; de Rijke, M.

    2009-01-01

    An important application of semantic web technology is recognizing human-defined concepts in text. Query transformation is a strategy often used in search engines to derive queries that are able to return more useful search results than the original query and most popular search engines provide

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Avogadro: an advanced semantic chemical editor, visualization, and analysis platform.

    Science.gov (United States)

    Hanwell, Marcus D; Curtis, Donald E; Lonie, David C; Vandermeersch, Tim; Zurek, Eva; Hutchison, Geoffrey R

    2012-08-13

    The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types. The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API) with three-dimensional visualization capabilities; and has direct applications to research and education in the fields of chemistry, physics, materials science, and biology. The Avogadro application provides a rich graphical interface using dynamically loaded plugins through the library itself. The application and library can each be extended by implementing a plugin module in C++ or Python to explore different visualization techniques, build/manipulate molecular structures, and interact with other programs. We describe some example extensions, one which uses a genetic algorithm to find stable crystal structures, and one which interfaces with the PackMol program to create packed, solvated structures for molecular dynamics simulations. The 1.0 release series of Avogadro is the main focus of the results discussed here. Avogadro offers a semantic chemical builder and platform for visualization and analysis. For users, it offers an easy-to-use builder, integrated support for downloading from common databases such as PubChem and the Protein Data Bank, extracting chemical data from a wide variety of formats, including computational chemistry output, and native, semantic support for the CML file format. For developers, it can be easily extended via a powerful

  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. Altered structure-function relations of semantic processing in youths with high-functioning autism: a combined diffusion and functional MRI study.

    Science.gov (United States)

    Lo, Yu-Chun; Chou, Tai-Li; Fan, Li-Ying; Gau, Susan Shur-Fen; Chiu, Yen-Nan; Tseng, Wen-Yih Isaac

    2013-12-01

    Deficits in language and communication are among the core symptoms of autism, a common neurodevelopmental disorder with long-term impairment. Despite the striking nature of the autistic language impairment, knowledge about its corresponding alterations in the brain is still evolving. We hypothesized that the dual stream language network is altered in autism, and that this alteration could be revealed by changes in the relationships between microstructural integrity and functional activation. The study recruited 20 right-handed male youths with autism and 20 carefully matched individually, typically developing (TD) youths. Microstructural integrity of the left dorsal and left ventral pathways responsible for language processing and the functional activation of the connected brain regions were investigated by using diffusion spectrum imaging and functional magnetic resonance imaging of a semantic task, respectively. Youths with autism had significantly poorer language function, and lower functional activation in left dorsal and left ventral regions of the language network, compared with TD youths. The TD group showed a significant correlation of the functional activation of the left dorsal region with microstructural integrity of the left ventral pathway, whereas the autism group showed a significant correlation of the functional activation of the left ventral region with microstructural integrity of the left dorsal pathway, and moreover verbal comprehension index was correlated with microstructural integrity of the left ventral pathway. These altered structure-function relationships in autism suggest possible involvement of the dual pathways in supporting deficient semantic processing. © 2013 International Society for Autism Research, Wiley Periodicals, Inc.

  7. 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.

  8. A Semantic Map for Evaluating Creativity

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; Wolf, Roger A.; Schmettow, Martin; Nazareth, Deniece; Toivonen, Hannu; Colton, Simon; Cook, Michael; Ventura, Dan

    2015-01-01

    We present a semantic map of words related with creativity. The aim is to empirically derive terms which can be used to rate processes or products of computational creativity. The words in the map are based on association studies performed by human subjects and augmented with words derived from the

  9. Integrating Multiple On-line Knowledge Bases for Disease-Lab Test Relation Extraction.

    Science.gov (United States)

    Zhang, Yaoyun; Soysal, Ergin; Moon, Sungrim; Wang, Jingqi; Tao, Cui; Xu, Hua

    2015-01-01

    A computable knowledge base containing relations between diseases and lab tests would be a great resource for many biomedical informatics applications. This paper describes our initial step towards establishing a comprehensive knowledge base of disease and lab tests relations utilizing three public on-line resources. LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase. Disease and lab test concepts are identified using MetaMap and relations between diseases and lab tests are determined based on source-specific rules. Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%. Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book. Moreover, we found additional disease-lab test relations from on-line resources, indicating they are complementary to existing reference books for building a comprehensive disease and lab test relation knowledge base.

  10. A crowdsourcing workflow for extracting chemical-induced disease relations from free text

    Science.gov (United States)

    Li, Tong Shu; Bravo, Àlex; Furlong, Laura I.; Good, Benjamin M.; Su, Andrew I.

    2016-01-01

    Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505 F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available at https://github.com/SuLab/crowd_cid_relex Database URL: https://github.com/SuLab/crowd_cid_relex PMID:27087308

  11. 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....

  12. 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

  13. Achyrocline satureioides (Lam. D.C. Hydroalcoholic Extract Inhibits Neutrophil Functions Related to Innate Host Defense

    Directory of Open Access Journals (Sweden)

    Eric Diego Barioni

    2013-01-01

    Full Text Available Achyrocline satureioides (Lam. D.C. is a herb native to South America, and its inflorescences are popularly employed to treat inflammatory diseases. Here, the effects of the in vivo actions of the hydroalcoholic extract obtained from inflorescences of A. satureioides on neutrophil trafficking into inflamed tissue were investigated. Male Wistar rats were orally treated with A. satureioides extract, and inflammation was induced one hour later by lipopolysaccharide injection into the subcutaneous tissue. The number of leukocytes and the amount of chemotactic mediators were quantified in the inflammatory exudate, and adhesion molecule and toll-like receptor 4 (TLR-4 expressions and phorbol-myristate-acetate- (PMA- stimulated oxidative burst were quantified in circulating neutrophils. Leukocyte-endothelial interactions were quantified in the mesentery tissue. Enzymes and tissue morphology of the liver and kidney were evaluated. Treatment with A. satureioides extract reduced neutrophil influx and secretion of leukotriene B4 and CINC-1 in the exudates, the number of rolling and adhered leukocytes in the mesentery postcapillary venules, neutrophil L-selectin, β2-integrin and TLR-4 expression, and oxidative burst, but did not cause an alteration in the morphology and activities of liver and kidney. Together, the data show that A. satureioides extract inhibits neutrophil functions related to the innate response and does not cause systemic toxicity.

  14. Repression of calcitonin gene-related peptide expression in trigeminal neurons by a Theobroma cacao extract.

    Science.gov (United States)

    Abbey, Marcie J; Patil, Vinit V; Vause, Carrie V; Durham, Paul L

    2008-01-17

    Cocoa bean preparations were first used by the ancient Maya and Aztec civilizations of South America to treat a variety of medical ailments involving the cardiovascular, gastrointestinal, and nervous systems. Diets rich in foods containing abundant polyphenols, as found in cocoa, underlie the protective effects reported in chronic inflammatory diseases. Release of calcitonin gene-related peptide (CGRP) from trigeminal nerves promotes inflammation in peripheral tissues and nociception. To determine whether a methanol extract of Theobroma cacao L. (Sterculiaceae) beans enriched for polyphenols could inhibit CGRP expression, both an in vitro and an in vivo approach was taken. Treatment of rat trigeminal ganglia cultures with depolarizing stimuli caused a significant increase in CGRP release that was repressed by pretreatment with Theobroma cacao extract. Pretreatment with Theobroma cacao was also shown to block the KCl- and capsaicin-stimulated increases in intracellular calcium. Next, the effects of Theobroma cacao on CGRP levels were determined using an in vivo model of temporomandibular joint (TMJ) inflammation. Capsaicin injection into the TMJ capsule caused an ipsilateral decrease in CGRP levels. Theobroma cacao extract injected into the TMJ capsule 24h prior to capsaicin treatment repressed the stimulatory effects of capsaicin. Our results demonstrate that Theobroma cacao extract can repress stimulated CGRP release by a mechanism that likely involves blockage of calcium channel activity. Furthermore, our findings suggest that the beneficial effects of diets rich in cocoa may include suppression of sensory trigeminal nerve activation.

  15. 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.

  16. 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)

  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. Intuitions and Competence in Formal Semantics

    Directory of Open Access Journals (Sweden)

    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.

  19. SEMANTIC DERIVATION OF BORROWINGS

    Directory of Open Access Journals (Sweden)

    Shigapova, F.F.

    2017-09-01

    Full Text Available The author carried out the contrastive analysis of the word спикер borrowed into Russian from English and the English word speaker. The findings of the analysis include confirm (1 different derivational abilities and functions of the borrowed word and the native word; (2 distinctive features in the definitions, i.e. semantic structures, registered in monolingual non-abridged dictionaries; (3 heterogeneous parameters of frequencies recorded in the National Corpus of the Russian language and the British National Corpus; (4 absence of bilingual equivalent collocations with words спикер and speaker. The collocations with words studied revealed new lexical and connotative senses in the meaning of the word. Relevance of the study conducted is justified by the new facts revealed about the semantic adaptation of the borrowed word in the system of the Russian language and its paradigmatic and syntagmatic connections in the system of the recipient language.

  20. The semantics of English Borrowings in Arabic Media Language: The case of Arab Gulf States Newspapers

    Directory of Open Access Journals (Sweden)

    Anwar A. H. Al-Athwary

    2016-07-01

    Full Text Available The present paper investigates the semantics of English loanwords in Arabic media language (AML. The loanword data are collected from a number of Arab Gulf states newspapers (AGSNs. They  are analyzed semantically from the points of view of semantic change, semantic domains, and the phenomenon of synonymy resulting from lexical borrowing. The semantic analysis has revealed that AML borrowings from English occur in fifteen distinctive semantic domains. Domains that are related to terms of technical and scientific nature are found ranking much higher (9% - 18% than those domains containing nontechnical elements (1% - 8% with the computer and technology category (18% is the most dominant domain. Almost all common mechanisms of semantic change (extension, restriction, amelioration, pejoration, and metaphorical extension are found at work in the context of AML borrowings. The tendency of semantic change in the overwhelming majority of AML borrowings is towards restriction.  Factors like need, semantic similarity, and factors of social and psychological considerations (e.g. prestige, taboo seem to be the potent factors at interplay in semantic change. The first two, i.e. need and semantic similarity, are the most common reasons in most types of semantic change. The problem of synonymy lies in those loanwords that have “Arabic equivalents” in the language. The study claims that this phenomenon could be attributed to the two simultaneous processes of lexical borrowing and?ištiqa:q (the modern efforts of deriving equivalent neologisms.

  1. Characterization of Temporal Semantic Shifts of Peer-to-Peer Communication in a Health-Related Online Community: Implications for Data-driven Health Promotion.

    Science.gov (United States)

    Sridharan, Vishnupriya; Cohen, Trevor; Cobb, Nathan; Myneni, Sahiti

    2016-01-01

    With online social platforms gaining popularity as venues of behavior change, it is important to understand the ways in which these platforms facilitate peer interactions. In this paper, we characterize temporal trends in user communication through mapping of theoretically-linked semantic content. We used qualitative coding and automated text analysis to assign theoretical techniques to peer interactions in an online community for smoking cessation, subsequently facilitating temporal visualization of the observed techniques. Results indicate manifestation of several behavior change techniques such as feedback and monitoring' and 'rewards'. Automated methods yielded reasonable results (F-measure=0.77). Temporal trends among relapsers revealed reduction in communication after a relapse event. This social withdrawal may be attributed to failure guilt after the relapse. Results indicate significant change in thematic categories such as 'social support', 'natural consequences', and 'comparison of outcomes' pre and post relapse. Implications for development of behavioral support technologies that promote long-term abstinence are discussed.

  2. Semantically Enhanced Recommender Systems

    Science.gov (United States)

    Ruiz-Montiel, Manuela; Aldana-Montes, José F.

    Recommender Systems have become a significant area in the context of web personalization, given the large amount of available data. Ontologies can be widely taken advantage of in recommender systems, since they provide a means of classifying and discovering of new information about the items to recommend, about user profiles and even about their context. We have developed a semantically enhanced recommender system based on this kind of ontologies. In this paper we present a description of the proposed system.

  3. YAdumper: extracting and translating large information volumes from relational databases to structured flat files.

    Science.gov (United States)

    Fernández, José M; Valencia, Alfonso

    2004-10-12

    Downloading the information stored in relational databases into XML and other flat formats is a common task in bioinformatics. This periodical dumping of information requires considerable CPU time, disk and memory resources. YAdumper has been developed as a purpose-specific tool to deal with the integral structured information download of relational databases. YAdumper is a Java application that organizes database extraction following an XML template based on an external Document Type Declaration. Compared with other non-native alternatives, YAdumper substantially reduces memory requirements and considerably improves writing performance.

  4. Insensitive Enough Semantics

    Directory of Open Access Journals (Sweden)

    Richard Vallée

    2006-06-01

    Full Text Available According to some philosophers, sentences like (1 “It is raining” and (2 “John is ready” are context sensitive sentences even if they do not contain indexicals or demonstratives. That view initiated a context sensitivity frenzy. Cappelen and Lepore (2005 summarize the frenzy by the slogan “Every sentence is context sensitive” (Insensitive Semantics, p. 6, note 5. They suggest a view they call Minimalism according to which the truth conditions of utterances of sentences like (1/(2 are exactly what Convention T gives you. I will distinguish different propositions, and refocus semantics on sentences. As distinct from what the protagonists in the ongoing debate think, I argue that the content or truth conditions of utterances of both context sensitive sentences and sentences like (1/(2 are not interesting from a semantic point of view, and that the problem sentences like (1/(2 raises is not about context sensitivity or context insensitivity of sentences, but relevance of the content of utterances.

  5. 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

  6. On a syntactic-semantic model with the locative case

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    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

  7. The Semantic Analysis of Icon

    Directory of Open Access Journals (Sweden)

    m Piravivanak

    2012-03-01

    Full Text Available "Eikon" (Greek word or "Imago" (Latin word signifies a kind of similarity or "likeness". In Plato’s philosophy, this term implies "likeness" of appearance to pattern or symbol. In semantic analysis of icon, which is correlated with Idea, we can find factors such as "perception", "imagination", "likeness", "imitation" (Mimesis, "imaginary ideas", that is, it is not possible to reduce icon to a material picture because it is supported by cultural (symbolic, perceptual and conceptual sources. The process in which an icon is established indicates a special relation between icon and imaginary ideas that is supported by symbolic sources. Then, it is not possible to regard icon as a material picture because icon is an icon of a symbol which is able to play its role visibly in relation to a symbol.

  8. Semantic Annotation of Unstructured Documents Using Concepts Similarity

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    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.

  9. Microfabricated Devices for Sample Extraction, Concentrations, and Related Sample Processing Technologies

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Gang; Lin, Yuehe

    2006-12-01

    This is an invited book chapter. As with other analytical techniques, sample pretreatments, sample extraction, sample introduction, and related techniques are of extreme importance for micro-electro-mechanical systems (MEMS). Bio-MEMS devices and systems start with a sampling step. The biological sample then usually undergoes some kinds of sample preparation steps before the actual analysis. These steps may involve extracting the target sample from its matrix, removing interferences from the sample, derivatizing the sample to detectable species, or performing a sample preconcentration step. The integration of the components for sample pretreatment into microfluidic devices represents one of the remaining the bottle-neck towards achieving true miniaturized total analysis systems (?TAS). This chapter provides a thorough state-of-art of the developments in this field to date.

  10. Hierarchical Semantic Model of Geovideo

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    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.

  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. 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,…

  13. 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

  14. Survey of semantic modeling techniques

    Energy Technology Data Exchange (ETDEWEB)

    Smith, C.L.

    1975-07-01

    The analysis of the semantics of programing languages was attempted with numerous modeling techniques. By providing a brief survey of these techniques together with an analysis of their applicability for answering semantic issues, this report attempts to illuminate the state-of-the-art in this area. The intent is to be illustrative rather than thorough in the coverage of semantic models. A bibliography is included for the reader who is interested in pursuing this area of research in more detail.

  15. Semantic multimedia analysis and processing

    CERN Document Server

    Spyrou, Evaggelos; Mylonas, Phivos

    2014-01-01

    Broad in scope, Semantic Multimedia Analysis and Processing provides a complete reference of techniques, algorithms, and solutions for the design and the implementation of contemporary multimedia systems. Offering a balanced, global look at the latest advances in semantic indexing, retrieval, analysis, and processing of multimedia, the book features the contributions of renowned researchers from around the world. Its contents are based on four fundamental thematic pillars: 1) information and content retrieval, 2) semantic knowledge exploitation paradigms, 3) multimedia personalization, and 4)

  16. Drought Resilience of Water Supplies for Shale Gas Extraction and Related Power Generation in Texas

    Science.gov (United States)

    Reedy, R. C.; Scanlon, B. R.; Nicot, J. P.; Uhlman, K.

    2014-12-01

    There is considerable concern about water availability to support energy production in Texas, particularly considering that many of the shale plays are in semiarid areas of Texas and the state experienced the most extreme drought on record in 2011. The Eagle Ford shale play provides an excellent case study. Hydraulic fracturing water use for shale gas extraction in the play totaled ~ 12 billion gallons (bgal) in 2012, representing ~7 - 10% of total water use in the 16 county play area. The dominant source of water is groundwater which is not highly vulnerable to drought from a recharge perspective because water is primarily stored in the confined portion of aquifers that were recharged thousands of years ago. Water supply drought vulnerability results primarily from increased water use for irrigation. Irrigation water use in the Eagle Ford play was 30 billion gallons higher in the 2011 drought year relative to 2010. Recent trends toward increased use of brackish groundwater for shale gas extraction in the Eagle Ford also reduce pressure on fresh water resources. Evaluating the impacts of natural gas development on water resources should consider the use of natural gas in power generation, which now represents 50% of power generation in Texas. Water consumed in extracting the natural gas required for power generation is equivalent to ~7% of the water consumed in cooling these power plants in the state. However, natural gas production from shale plays can be overall beneficial in terms of water resources in the state because natural gas combined cycle power generation decreases water consumption by ~60% relative to traditional coal, nuclear, and natural gas plants that use steam turbine generation. This reduced water consumption enhances drought resilience of power generation in the state. In addition, natural gas combined cycle plants provide peaking capacity that complements increasing renewable wind generation which has no cooling water requirement. However, water

  17. 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

  18. 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.

  19. System semantics of explanatory dictionaries

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    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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. A crowdsourcing workflow for extracting chemical-induced disease relations from free text.

    Science.gov (United States)

    Li, Tong Shu; Bravo, Àlex; Furlong, Laura I; Good, Benjamin M; Su, Andrew I

    2016-01-01

    Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available athttps://github.com/SuLab/crowd_cid_relexDatabase URL:https://github.com/SuLab/crowd_cid_relex. © The Author(s) 2016. Published by Oxford University Press.

  5. Ginseng Berry Extract Supplementation Improves Age-Related Decline of Insulin Signaling in Mice

    Directory of Open Access Journals (Sweden)

    Eunhui Seo

    2015-04-01

    Full Text Available The aim of this study was to evaluate the effects of ginseng berry extract on insulin sensitivity and associated molecular mechanisms in aged mice. C57BL/6 mice (15 months old were maintained on a regular diet (CON or a regular diet supplemented with 0.05% ginseng berry extract (GBD for 24 or 32 weeks. GBD-fed mice showed significantly lower serum insulin levels (p = 0.016 and insulin resistance scores (HOMA-IR (p = 0.012, suggesting that GBD improved insulin sensitivity. Pancreatic islet hypertrophy was also ameliorated in GBD-fed mice (p = 0.007. Protein levels of tyrosine phosphorylated insulin receptor substrate (IRS-1 (p = 0.047, and protein kinase B (AKT (p = 0.037, were up-regulated in the muscle of insulin-injected GBD-fed mice compared with CON-fed mice. The expressions of forkhead box protein O1 (FOXO1 (p = 0.036 and peroxisome proliferator-activated receptor gamma (PPARγ (p = 0.032, which are known as aging- and insulin resistance-related genes, were also increased in the muscle of GBD-fed mice. We conclude that ginseng berry extract consumption might increase activation of IRS-1 and AKT, contributing to the improvement of insulin sensitivity in aged mice.

  6. Characteristic extraction in numerical relativity: binary black hole merger waveforms at null infinity

    Energy Technology Data Exchange (ETDEWEB)

    Reisswig, C; Pollney, D [Max-Planck-Institut fuer Gravitationsphysik, Albert-Einstein-Institut, 14476 Golm (Germany); Bishop, N T [Department of Mathematics, Rhodes University, Grahamstown 6140 (South Africa); Szilagyi, B [Theoretical Astrophysics, California Institute of Technology, Pasadena, CA 91125 (United States)

    2010-04-07

    The accurate modeling of gravitational radiation is a key issue for gravitational wave astronomy. As simulation codes reach higher accuracy, systematic errors inherent in current numerical relativity wave extraction methods become evident, and may lead to a wrong astrophysical interpretation of the data. In this paper, we give a detailed description of the Cauchy-characteristic extraction technique applied to binary black hole inspiral and merger evolutions to obtain gravitational waveforms that are defined unambiguously, that is, at future null infinity. By this method, we remove finite-radius approximations and the need to extrapolate data from the near zone. Further, we demonstrate that the method is free of gauge effects and thus is affected only by numerical error. Various consistency checks reveal that energy and angular momentum are conserved to high precision and agree very well with extrapolated data. In addition, we revisit the computation of the gravitational recoil and find that finite-radius extrapolation very well approximates the result at J{sup +}. However, the (non-convergent) systematic differences in the extrapolated data are of the same order of magnitude as the (convergent) discretization error of the Cauchy evolution, thus highlighting the need for correct wave extraction.

  7. Estrogen-related receptor gamma disruption of source water and drinking water treatment processes extracts.

    Science.gov (United States)

    Li, Na; Jiang, Weiwei; Rao, Kaifeng; Ma, Mei; Wang, Zijian; Kumaran, Satyanarayanan Senthik

    2011-01-01

    Environmental chemicals in drinking water can impact human health through nuclear receptors. Additionally, estrogen-related receptors (ERRs) are vulnerable to endocrine-disrupting effects. To date, however, ERR disruption of drinking water potency has not been reported. We used ERRgamma two-hybrid yeast assay to screen ERRgamma disrupting activities in a drinking water treatment plant (DWTP) located in north China and in source water from a reservoir, focusing on agonistic, antagonistic, and inverse agonistic activity to 4-hydroxytamoxifen (4-OHT). Water treatment processes in the DWTP consisted of pre-chlorination, coagulation, coal and sand filtration, activated carbon filtration, and secondary chlorination processes. Samples were extracted by solid phase extraction. Results showed that ERRgamma antagonistic activities were found in all sample extracts, but agonistic and inverse agonistic activity to 4-OHT was not found. When calibrated with the toxic equivalent of 4-OHT, antagonistic effluent effects ranged from 3.4 to 33.1 microg/L. In the treatment processes, secondary chlorination was effective in removing ERRgamma antagonists, but the coagulation process led to significantly increased ERRgamma antagonistic activity. The drinking water treatment processes removed 73.5% of ERRgamma antagonists. To our knowledge, the occurrence of ERRgamma disruption activities on source and drinking water in vitro had not been reported previously. It is vital, therefore, to increase our understanding of ERRy disrupting activities in drinking water.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. Connectionism and Compositional Semantics

    Science.gov (United States)

    1989-05-01

    can use their hidden layers to learn difficult discriminations. such as panty or the Penzias two clumps/three clumps problem, where the output is...sauce." For novel sentences that are similar to the training sentences (e.g., train on "the girl hit the boy," test on -the boy hit the girl "), the...overridden by semantic considerations. as in this example from Wendy Lehnert (personal communicanon): (5) John saw the girl with the telescope in a red

  18. A Semantics of Synchronization.

    Science.gov (United States)

    1980-09-01

    suggestion of having very hungry philosophers. One can easily imagine the complexity of the equivalent implementation using semaphores . Synchronization types...Edinburgh, July 1978. [STAR79] Stark, E.W., " Semaphore Primitives and Fair Mutual Exclusion," TM-158, Laboratory for Computer Science, M.I.T., Cambridge...AD-AQ91 015 MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR COMPUTE--ETC F/S 9/2 A SEMANTICS OF SYNCHRONIZATION .(U) .C SEP 80 C A SEAQUIST N00015-75

  19. Semantics, Conceptual Role

    OpenAIRE

    Block, Ned

    1997-01-01

    According to Conceptual Role Semantics ("CRS"), the meaning of a representation is the role of that representation in the cognitive life of the agent, e.g. in perception, thought and decision-making. It is an extension of the well known "use" theory of meaning, according to which the meaning of a word is its use in communication and more generally, in social interaction. CRS supplements external use by including the role of a symbol inside a computer or a brain. The uses appealed to are not j...

  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. 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.

  2. 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.

  3. 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

  4. 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

  5. A Generalization of Inquisitive Semantics

    Czech Academy of Sciences Publication Activity Database

    Punčochář, Vít

    2016-01-01

    Roč. 45, č. 4 (2016), s. 399-428 ISSN 0022-3611 R&D Projects: GA ČR(CZ) GA13-21076S Institutional support: RVO:67985955 Keywords : Intuitionistic logic * Superintuitionistic logics * Inquisitive logic * Topological semantics * Kripke semantics * Disjunction Subject RIV: AA - Philosophy ; Religion

  6. The Problem of Naturalizing Semantics.

    Science.gov (United States)

    Sullivan, Arthur

    2000-01-01

    Investigates conceptual barriers prevalent in the works of both proponents and opponents of semantic naturalism. Searches for a tenable definition of naturalism according to which one can be a realist, a non-reductionist, and a naturalist about semantic content. (Author/VWL)

  7. Advancing translational research with the Semantic Web.

    Science.gov (United States)

    Ruttenberg, Alan; Clark, Tim; Bug, William; Samwald, Matthias; Bodenreider, Olivier; Chen, Helen; Doherty, Donald; Forsberg, Kerstin; Gao, Yong; Kashyap, Vipul; Kinoshita, June; Luciano, Joanne; Marshall, M Scott; Ogbuji, Chimezie; Rees, Jonathan; Stephens, Susie; Wong, Gwendolyn T; Wu, Elizabeth; Zaccagnini, Davide; Hongsermeier, Tonya; Neumann, Eric; Herman, Ivan; Cheung, Kei-Hoi

    2007-05-09

    A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base

  8. 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.

  9. PSSRdb: a relational database of polymorphic simple sequence repeats extracted from prokaryotic genomes.

    Science.gov (United States)

    Kumar, Pankaj; Chaitanya, Pasumarthy S; Nagarajaram, Hampapathalu A

    2011-01-01

    PSSRdb (Polymorphic Simple Sequence Repeats database) (http://www.cdfd.org.in/PSSRdb/) is a relational database of polymorphic simple sequence repeats (PSSRs) extracted from 85 different species of prokaryotes. Simple sequence repeats (SSRs) are the tandem repeats of nucleotide motifs of the sizes 1-6 bp and are highly polymorphic. SSR mutations in and around coding regions affect transcription and translation of genes. Such changes underpin phase variations and antigenic variations seen in some bacteria. Although SSR-mediated phase variation and antigenic variations have been well-studied in some bacteria there seems a lot of other species of prokaryotes yet to be investigated for SSR mediated adaptive and other evolutionary advantages. As a part of our on-going studies on SSR polymorphism in prokaryotes we compared the genome sequences of various strains and isolates available for 85 different species of prokaryotes and extracted a number of SSRs showing length variations and created a relational database called PSSRdb. This database gives useful information such as location of PSSRs in genomes, length variation across genomes, the regions harboring PSSRs, etc. The information provided in this database is very useful for further research and analysis of SSRs in prokaryotes.

  10. Thematic orders and the comprehension of subject-extracted relative clauses in Mandarin Chinese

    Directory of Open Access Journals (Sweden)

    Chien-Jer Charles Lin

    2015-09-01

    Full Text Available This study investigates the comprehension of three kinds of subject-extracted relative clauses (SRs in Mandarin Chinese: standard SRs, relative clauses involving the disposal ba construction (‘disposal SRs’, and relative clauses involving the long passive bei constructions (‘passive SRs’. In a self-paced reading experiment, the regions before the relativizer (where the sentential fragments are temporarily ambiguous showed reading patterns consistent with expectation-based incremental processing: standard SRs (with the highest constructional frequency and the least complex syntactic structure were processed faster than the other two variants. However, in the regions after the relativizer and the head noun (where the existence of a relative clause is unambiguously indicated, a top-down global effect of thematic ordering was observed: passive SRs (whose thematic role order conforms to the canonical thematic order of Chinese were read faster than both the standard SRs and the disposal SRs. Taken together, these results suggest that two expectation-based processing factors are involved in the comprehension of Chinese relative clauses, including both the structural probabilities of pre-relativizer constituents and the overall surface thematic orders in the relative clauses.

  11. 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

  12. 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

  13. 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.

  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. 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...

  16. 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

  17. 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.

  18. 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.

  19. On semantics and applications of guarded recursion

    DEFF Research Database (Denmark)

    Bizjak, Aleš

    2016-01-01

    denotational model and a logic for reasoning about program equivalence. In the last three chapters we study syntax and semantics of a dependent type theory with a family of later modalities indexed by the set of clocks, and clock quantifiers. In the fourth and fifth chapters we provide two model constructions......In this dissertation we study applications and semantics of guarded recursion, which is a method for ensuring that self-referential descriptions of objects define a unique object. The first two chapters are devoted to applications. We use guarded recursion, first in the form of explicit step......-indexing and then in the form of the internal language of particular sheaf topos, to construct logical relations for reasoning about contextual approximation of probabilistic and nondeterministic programs. These logical relations are sound and complete and useful for showing a range of example equivalences. In the third...

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. Specifying semantic information on functional requirements

    OpenAIRE

    YAO, WUPING

    2012-01-01

    Requirements engineering is a challenging process in software development projects. Requirements, in general, are documented in natural language. They often have issues related to ambiguity, completeness and consistency. How to improve the quality of requirements documentation remains a classic research topic. This research aims at improving the way of editing and documenting functional requirements. We propose a meta-model to specify the semantic information of functional requirements, and d...

  6. 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.

  7. Extracting a kinetic relation from the dynamics of a bistable chain

    International Nuclear Information System (INIS)

    Zhao, Qingze; Purohit, Prashant K

    2014-01-01

    We integrate Newton's second law for a chain of masses and bistable springs with a spinodal region with the goal of extracting a kinetic relation for propagating phase boundaries. Our numerical experiments correspond to the impact on a bar made of phase changing material. By reading off the spring extensions ahead and behind the phase boundaries in our numerical experiments, we compute a driving force and plot it as a function of the phase boundary velocity to get a kinetic relation. We then show that this kinetic relation results in solutions to Riemann problems in continuum bars that agree with the corresponding numerical experiments on the discrete mass–spring chain. We also integrate Langevin's equations of motion for the same chain of masses and springs to account for the presence of a heat bath at a fixed temperature. We find that the xt-plane looks similar to the purely mechanical numerical experiments at low temperatures but at high temperatures there is an increased incidence of random nucleation events. Using results from both impact and Riemann problems, we show that the kinetic relation is a function of the bath temperature. (paper)

  8. 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...

  9. Semantic integration of gene expression analysis tools and data sources using software connectors

    Science.gov (United States)

    2013-01-01

    Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools

  10. 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

  11. 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

  12. Mercury exposure of workers and health problems related with small-scale gold panning and extraction

    International Nuclear Information System (INIS)

    Khan, S.; Shah, M.T.; Din, I.U.; Rehman, S.

    2012-01-01

    This study was conducted to investigate mercury (Hg) exposure and health problems related to small-scale gold panning and extraction (GPE) in the northern Pakistan. Urine and blood samples of occupational and non-occupational persons were analyzed for total Hg, while blood's fractions including red blood cells and plasma were analyzed for total Hg and its inorganic and organic species. The concentrations of Hg in urine and blood samples were significantly (P<0.01) higher in occupational persons as compared to non-occupational and exceeded the permissible limits set by World Health Organization (WHO) and United State Environmental Protection Agency (US-EPA). Furthermore, the data indicated that numerous health problems were present in occupational persons involved in GPE. (author)

  13. 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…

  14. Communication of Semantic Properties

    DEFF Research Database (Denmark)

    Lenau, Torben Anker; Boelskifte, Per

    2004-01-01

    The selection of materials and planning for production play a key role for the design of physical products. Product function, appearance and expression are influenced by the chosen materials and how they are shaped. However these properties are not carried by the material itself, but by the speci......The selection of materials and planning for production play a key role for the design of physical products. Product function, appearance and expression are influenced by the chosen materials and how they are shaped. However these properties are not carried by the material itself...... processes. This working paper argues for the need for a commonly accepted terminology used to communicate semantic product properties. Designers and others involved in design processes are dependent of a sharp and clear verbal communication. Search facilities in computer programs for product and material...

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. Semantic acquisition games harnessing manpower for creating semantics

    CERN Document Server

    Šimko, Jakub

    2014-01-01

    A comprehensive and extensive review of state-of-the-art in semantics acquisition game (SAG) design A set of design patterns for SAG designers A set of case studies (real SAG projects) demonstrating the use of SAG design patterns

  20. Extract the Relational Information of Static Features and Motion Features for Human Activities Recognition in Videos

    Directory of Open Access Journals (Sweden)

    Li Yao

    2016-01-01

    Full Text Available Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use a k-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm’s projective function. We test our work on the several datasets and obtain very promising results.

  1. 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

  2. Evaluation of Rare Earth Element Extraction from North Dakota Coal-Related Feed Stocks

    Science.gov (United States)

    Laudal, Daniel A.

    The rare earth elements consist of the lanthanide series of elements with atomic numbers from 57-71 and also include yttrium and scandium. Due to their unique properties, rare earth elements are crucial materials in an incredible array of consumer goods, energy system components and military defense applications. However, the global production and entire value chain for rare earth elements is dominated by China, with the U.S. currently 100% import reliant for these critical materials. Traditional mineral ores including previously mined deposits in the U.S., however, have several challenges. Chief among these is that the content of the most critical and valuable of the rare earths are deficient, making mining uneconomical. Further, the supply of these most critical rare earths is nearly 100% produced in China from a single resource that is only projected to last another 10 to 20 years. The U.S. currently considers the rare earths market an issue of national security. It is imperative that alternative domestic sources of rare earths be identified and methods developed to produce them. Recently, coal and coal byproducts have been identified as one of these promising alternative resources. This dissertation details a study on evaluation of the technical and economic feasibility of rare earth element recovery from North Dakota lignite coal and lignite-related feedstocks. There were four major goals of this study: i) identify lignite or lignite-related feedstocks with total rare earth element content above 300 parts per million, a threshold dictated by the agency who funded this research as the minimum for economic viability, ii) determine the geochemistry of the feedstocks and understand the forms and modes of occurrence of the rare earth elements, information necessary to inform the development of extraction and concentration methods, iii) identify processing methods to concentrate the rare earth elements from the feedstocks to a target of two weight percent, a value

  3. Language and culture modulate online semantic processing.

    Science.gov (United States)

    Ellis, Ceri; Kuipers, Jan R; Thierry, Guillaume; Lovett, Victoria; Turnbull, Oliver; Jones, Manon W

    2015-10-01

    Language has been shown to influence non-linguistic cognitive operations such as colour perception, object categorization and motion event perception. Here, we show that language also modulates higher level processing, such as semantic knowledge. Using event-related brain potentials, we show that highly fluent Welsh-English bilinguals require significantly less processing effort when reading sentences in Welsh which contain factually correct information about Wales, than when reading sentences containing the same information presented in English. Crucially, culturally irrelevant information was processed similarly in both Welsh and English. Our findings show that even in highly proficient bilinguals, language interacts with factors associated with personal identity, such as culture, to modulate online semantic processing. © The Author (2015). Published by Oxford University Press.

  4. Congenital blindness improves semantic and episodic memory.

    Science.gov (United States)

    Pasqualotto, Achille; Lam, Jade S Y; Proulx, Michael J

    2013-05-01

    Previous studies reported that congenitally blind people possess superior verb-generation skills. Here we tested the impact of blindness on capacity and the fidelity of semantic memory by using a false memory paradigm. In the Deese-Roediger-McDermott paradigm, participants study lists of words that are all semantically related to a lure that is not presented. Subsequently, participants frequently recall the missing lure. We found that congenitally blind participants have enhanced memory performance for recalling the presented words and reduced false memories for the lure. The dissociation of memory capacity and fidelity provides further evidence for enhanced verbal ability in the blind, supported by their broader structural and functional brain reorganisation. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Bayesian natural language semantics and pragmatics

    CERN Document Server

    Zeevat, Henk

    2015-01-01

    The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice's contributions to pragmatics or in interpretation by abduction.

  6. Coordination in Categorical Compositional Distributional Semantics

    Directory of Open Access Journals (Sweden)

    Dimitri Kartsaklis

    2016-08-01

    Full Text Available An open problem with categorical compositional distributional semantics is the representation of words that are considered semantically vacuous from a distributional perspective, such as determiners, prepositions, relative pronouns or coordinators. This paper deals with the topic of coordination between identical syntactic types, which accounts for the majority of coordination cases in language. By exploiting the compact closed structure of the underlying category and Frobenius operators canonically induced over the fixed basis of finite-dimensional vector spaces, we provide a morphism as representation of a coordinator tensor, and we show how it lifts from atomic types to compound types. Linguistic intuitions are provided, and the importance of the Frobenius operators as an addition to the compact closed setting with regard to language is discussed.

  7. Odor identification: perceptual and semantic dimensions.

    Science.gov (United States)

    Cain, W S; de Wijk, R; Lulejian, C; Schiet, F; See, L C

    1998-06-01

    Five studies explored identification of odors as an aspect of semantic memory. All dealt in one way or another with the accessibility of acquired olfactory information. The first study examined stability and showed that, consistent with personal reports, people can fail to identify an odor one day yet succeed another. Failure turned more commonly to success than vice versa, and once success occurred it tended to recur. Confidence ratings implied that subjects generally knew the quality of their answers. Even incorrect names, though, often carried considerable information which sometimes reflected a semantic and sometimes a perceptual source of errors. The second study showed that profiling odors via the American Society of Testing and Materials list of attributes, an exercise in depth of processing, effected no increment in the identifiability/accessibility beyond an unelaborated second attempt at retrieval. The third study showed that subjects had only a weak ability to predict the relative recognizability of odors they had failed to identify. Whereas the strength of the feeling that they would 'know' an answer if offered choices did not associate significantly with performance for odors, it did for trivia questions. The fourth study demonstrated an association between ability to discriminate among one set of odors and to identify another, but this emerged only after subjects had received feedback about identity, which essentially changed the task to one of recognition and effectively stabilized access. The fifth study illustrated that feedback improves performance dramatically only for odors involved with it, but that mere retrieval leads to some improvement. The studies suggest a research agenda that could include supplemental use of confidence judgments both retrospectively and prospectively in the same subjects to indicate the amount of accessible semantic information; use of second and third guesses to examine subjects' simultaneously held hypotheses about

  8. 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.

  9. Episodic and Semantic Autobiographical Memory and Everyday Memory during Late Childhood and Early Adolescence

    OpenAIRE

    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 th...

  10. 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

  11. 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

  12. Semantic Knowledge Representation (SKR) API

    Data.gov (United States)

    U.S. Department of Health & Human Services — The SKR Project was initiated at NLM in order to develop programs to provide usable semantic representation of biomedical free text by building on resources...

  13. Problem Solving with General Semantics.

    Science.gov (United States)

    Hewson, David

    1996-01-01

    Discusses how to use general semantics formulations to improve problem solving at home or at work--methods come from the areas of artificial intelligence/computer science, engineering, operations research, and psychology. (PA)

  14. NASA and The Semantic Web

    Science.gov (United States)

    Ashish, Naveen

    2005-01-01

    We provide an overview of several ongoing NASA endeavors based on concepts, systems, and technology from the Semantic Web arena. Indeed NASA has been one of the early adopters of Semantic Web Technology and we describe ongoing and completed R&D efforts for several applications ranging from collaborative systems to airspace information management to enterprise search to scientific information gathering and discovery systems at NASA.

  15. Are Some Semantic Changes Predictable?

    DEFF Research Database (Denmark)

    Schousboe, Steen

    2010-01-01

      Historical linguistics is traditionally concerned with phonology and syntax. With the exception of grammaticalization - the development of auxiliary verbs, the syntactic rather than localistic use of prepositions, etc. - semantic change has usually not been described as a result of regular...... developments, but only as specific meaning changes in individual words. This paper will suggest some regularities in semantic change, regularities which, like sound laws, have predictive power and can be tested against recorded languages....

  16. Efficient computation of argumentation semantics

    CERN Document Server

    Liao, Beishui

    2013-01-01

    Efficient Computation of Argumentation Semantics addresses argumentation semantics and systems, introducing readers to cutting-edge decomposition methods that drive increasingly efficient logic computation in AI and intelligent systems. Such complex and distributed systems are increasingly used in the automation and transportation systems field, and particularly autonomous systems, as well as more generic intelligent computation research. The Series in Intelligent Systems publishes titles that cover state-of-the-art knowledge and the latest advances in research and development in intelligen

  17. 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.

  18. 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

  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. 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.