Enemies and Friends in the Neighborhood: Orthographic Similarity Effects in Semantic Categorization

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Pecher, Diane; Zeelenberg, Rene; Wagenmakers, Eric-Jan

2005-01-01

Studies investigating orthographic similarity effects in semantic tasks have produced inconsistent results. The authors investigated orthographic similarity effects in animacy decision and in contrast with previous studies, they took semantic congruency into account. In Experiments 1 and 2, performance to a target (cat) was better if a previously…

EVALUATION OF SEMANTIC SIMILARITY FOR SENTENCES IN NATURAL LANGUAGE BY MATHEMATICAL STATISTICS METHODS

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A. E. Pismak

2016-03-01

Full Text Available Subject of Research. The paper is focused on Wiktionary articles structural organization in the aspect of its usage as the base for semantic network. Wiktionary community references, article templates and articles markup features are analyzed. The problem of numerical estimation for semantic similarity of structural elements in Wiktionary articles is considered. Analysis of existing software for semantic similarity estimation of such elements is carried out; algorithms of their functioning are studied; their advantages and disadvantages are shown. Methods. Mathematical statistics methods were used to analyze Wiktionary articles markup features. The method of semantic similarity computing based on statistics data for compared structural elements was proposed.Main Results. We have concluded that there is no possibility for direct use of Wiktionary articles as the source for semantic network. We have proposed to find hidden similarity between article elements, and for that purpose we have developed the algorithm for calculation of confidence coefficients proving that each pair of sentences is semantically near. The research of quantitative and qualitative characteristics for the developed algorithm has shown its major performance advantage over the other existing solutions in the presence of insignificantly higher error rate. Practical Relevance. The resulting algorithm may be useful in developing tools for automatic Wiktionary articles parsing. The developed method could be used in computing of semantic similarity for short text fragments in natural language in case of algorithm performance requirements are higher than its accuracy specifications.

Thai Language Sentence Similarity Computation Based on Syntactic Structure and Semantic Vector

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Wang, Hongbin; Feng, Yinhan; Cheng, Liang

2018-03-01

Sentence similarity computation plays an increasingly important role in text mining, Web page retrieval, machine translation, speech recognition and question answering systems. Thai language as a kind of resources scarce language, it is not like Chinese language with HowNet and CiLin resources. So the Thai sentence similarity research faces some challenges. In order to solve this problem of the Thai language sentence similarity computation. This paper proposes a novel method to compute the similarity of Thai language sentence based on syntactic structure and semantic vector. This method firstly uses the Part-of-Speech (POS) dependency to calculate two sentences syntactic structure similarity, and then through the word vector to calculate two sentences semantic similarity. Finally, we combine the two methods to calculate two Thai language sentences similarity. The proposed method not only considers semantic, but also considers the sentence syntactic structure. The experiment result shows that this method in Thai language sentence similarity computation is feasible.

Web service discovery among large service pools utilising semantic similarity and clustering

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Chen, Fuzan; Li, Minqiang; Wu, Harris; Xie, Lingli

2017-03-01

With the rapid development of electronic business, Web services have attracted much attention in recent years. Enterprises can combine individual Web services to provide new value-added services. An emerging challenge is the timely discovery of close matches to service requests among large service pools. In this study, we first define a new semantic similarity measure combining functional similarity and process similarity. We then present a service discovery mechanism that utilises the new semantic similarity measure for service matching. All the published Web services are pre-grouped into functional clusters prior to the matching process. For a user's service request, the discovery mechanism first identifies matching services clusters and then identifies the best matching Web services within these matching clusters. Experimental results show that the proposed semantic discovery mechanism performs better than a conventional lexical similarity-based mechanism.

The semantic-similarity effect in children: influence of long-term knowledge on verbal short-term memory.

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Monnier, Catherine; Bonthoux, Françoise

2011-11-01

The present research was designed to highlight the relation between children's categorical knowledge and their verbal short-term memory (STM) performance. To do this, we manipulated the categorical organization of the words composing lists to be memorized by 5- and 9-year-old children. Three types of word list were drawn up: semantically similar context-dependent (CD) lists, semantically similar context-independent (CI) lists, and semantically dissimilar lists. In line with the procedure used by Poirier and Saint-Aubin (1995), the dissimilar lists were produced using words from the semantically similar lists. Both 5- and 9-year-old children showed better recall for the semantically similar CD lists than they did for the unrelated lists. In the semantic similar CI condition, semantic similarity enhanced immediate serial recall only at age 9 but contributed to item information memory both at ages 5 and 9. These results, which indicate a semantic influence of long-term memory (LTM) on serial recall from age 5, are discussed in the light of current models of STM. Moreover, we suggest that differences between results at 5 and 9 years are compatible with pluralist models of development. ©2011 The British Psychological Society.

Hierarchical Matching of Traffic Information Services Using Semantic Similarity

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Zongtao Duan

2018-01-01

Full Text Available Service matching aims to find the information similar to a given query, which has numerous applications in web search. Although existing methods yield promising results, they are not applicable for transportation. In this paper, we propose a multilevel matching method based on semantic technology, towards efficiently searching the traffic information requested. Our approach is divided into two stages: service clustering, which prunes candidate services that are not promising, and functional matching. The similarity at function level between services is computed by grouping the connections between the services into inheritance and noninheritance relationships. We also developed a three-layer framework with a semantic similarity measure that requires less time and space cost than existing method since the scale of candidate services is significantly smaller than the whole transportation network. The OWL_TC4 based service set was used to verify the proposed approach. The accuracy of offline service clustering reached 93.80%, and it reduced the response time to 651 ms when the total number of candidate services was 1000. Moreover, given the different thresholds for the semantic similarity measure, the proposed mixed matching model did better in terms of recall and precision (i.e., up to 72.7% and 80%, respectively, for more than 1000 services compared to the compared models based on information theory and taxonomic distance. These experimental results confirmed the effectiveness and validity of service matching for responding quickly and accurately to user queries.

A shortest-path graph kernel for estimating gene product semantic similarity

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Alvarez Marco A

2011-07-01

Full Text Available Abstract Background Existing methods for calculating semantic similarity between gene products using the Gene Ontology (GO often rely on external resources, which are not part of the ontology. Consequently, changes in these external resources like biased term distribution caused by shifting of hot research topics, will affect the calculation of semantic similarity. One way to avoid this problem is to use semantic methods that are "intrinsic" to the ontology, i.e. independent of external knowledge. Results We present a shortest-path graph kernel (spgk method that relies exclusively on the GO and its structure. In spgk, a gene product is represented by an induced subgraph of the GO, which consists of all the GO terms annotating it. Then a shortest-path graph kernel is used to compute the similarity between two graphs. In a comprehensive evaluation using a benchmark dataset, spgk compares favorably with other methods that depend on external resources. Compared with simUI, a method that is also intrinsic to GO, spgk achieves slightly better results on the benchmark dataset. Statistical tests show that the improvement is significant when the resolution and EC similarity correlation coefficient are used to measure the performance, but is insignificant when the Pfam similarity correlation coefficient is used. Conclusions Spgk uses a graph kernel method in polynomial time to exploit the structure of the GO to calculate semantic similarity between gene products. It provides an alternative to both methods that use external resources and "intrinsic" methods with comparable performance.

The Hofmethode: Computing Semantic Similarities between E-Learning Products

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Oliver Michel

2009-11-01

Full Text Available The key task in building useful e-learning repositories is to develop a system with an algorithm allowing users to retrieve information that corresponds to their specific requirements. To achieve this, products (or their verbal descriptions, i.e. presented in metadata need to be compared and structured according to the results of this comparison. Such structuring is crucial insofar as there are many search results that correspond to the entered keyword. The Hofmethode is an algorithm (based on psychological considerations to compute semantic similarities between texts and therefore offer a way to compare e-learning products. The computed similarity values are used to build semantic maps in which the products are visually arranged according to their similarities. The paper describes how the Hofmethode is implemented in the online database edulap, and how it contributes to help the user to explore the data in which he is interested.

Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products

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Mingxin Gan

2014-01-01

Full Text Available Successful applications of the gene ontology to the inference of functional relationships between gene products in recent years have raised the need for computational methods to automatically calculate semantic similarity between gene products based on semantic similarity of gene ontology terms. Nevertheless, existing methods, though having been widely used in a variety of applications, may significantly overestimate semantic similarity between genes that are actually not functionally related, thereby yielding misleading results in applications. To overcome this limitation, we propose to represent a gene product as a vector that is composed of information contents of gene ontology terms annotated for the gene product, and we suggest calculating similarity between two gene products as the relatedness of their corresponding vectors using three measures: Pearson’s correlation coefficient, cosine similarity, and the Jaccard index. We focus on the biological process domain of the gene ontology and annotations of yeast proteins to study the effectiveness of the proposed measures. Results show that semantic similarity scores calculated using the proposed measures are more consistent with known biological knowledge than those derived using a list of existing methods, suggesting the effectiveness of our method in characterizing functional relationships between gene products.

A Novel Approach to Semantic Similarity Measurement Based on a Weighted Concept Lattice: Exemplifying Geo-Information

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Jia Xiao

2017-11-01

Full Text Available The measurement of semantic similarity has been widely recognized as having a fundamental and key role in information science and information systems. Although various models have been proposed to measure semantic similarity, these models are not able effectively to quantify the weights of relevant factors that impact on the judgement of semantic similarity, such as the attributes of concepts, application context, and concept hierarchy. In this paper, we propose a novel approach that comprehensively considers the effects of various factors on semantic similarity judgment, which we name semantic similarity measurement based on a weighted concept lattice (SSMWCL. A feature model and network model are integrated together in SSMWCL. Based on the feature model, the combined weight of each attribute of the concepts is calculated by merging its information entropy and inclusion-degree importance in a specific application context. By establishing the weighted concept lattice, the relative hierarchical depths of concepts for comparison are computed according to the principle of the network model. The integration of feature model and network model enables SSMWCL to take account of differences in concepts more comprehensively in semantic similarity measurement. Additionally, a workflow of SSMWCL is designed to demonstrate these procedures and a case study of geo-information is conducted to assess the approach.

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

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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.

Right fusiform response patterns reflect visual object identity rather than semantic similarity.

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Bruffaerts, Rose; Dupont, Patrick; De Grauwe, Sophie; Peeters, Ronald; De Deyne, Simon; Storms, Gerrit; Vandenberghe, Rik

2013-12-01

We previously reported the neuropsychological consequences of a lesion confined to the middle and posterior part of the right fusiform gyrus (case JA) causing a partial loss of knowledge of visual attributes of concrete entities in the absence of category-selectivity (animate versus inanimate). We interpreted this in the context of a two-step model that distinguishes structural description knowledge from associative-semantic processing and implicated the lesioned area in the former process. To test this hypothesis in the intact brain, multi-voxel pattern analysis was used in a series of event-related fMRI studies in a total of 46 healthy subjects. We predicted that activity patterns in this region would be determined by the identity of rather than the conceptual similarity between concrete entities. In a prior behavioral experiment features were generated for each entity by more than 1000 subjects. Based on a hierarchical clustering analysis the entities were organised into 3 semantic clusters (musical instruments, vehicles, tools). Entities were presented as words or pictures. With foveal presentation of pictures, cosine similarity between fMRI response patterns in right fusiform cortex appeared to reflect both the identity of and the semantic similarity between the entities. No such effects were found for words in this region. The effect of object identity was invariant for location, scaling, orientation axis and color (grayscale versus color). It also persisted for different exemplars referring to a same concrete entity. The apparent semantic similarity effect however was not invariant. This study provides further support for a neurobiological distinction between structural description knowledge and processing of semantic relationships and confirms the role of right mid-posterior fusiform cortex in the former process, in accordance with previous lesion evidence. © 2013.

On fuzzy semantic similarity measure for DNA coding.

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Ahmad, Muneer; Jung, Low Tang; Bhuiyan, Md Al-Amin

2016-02-01

A coding measure scheme numerically translates the DNA sequence to a time domain signal for protein coding regions identification. A number of coding measure schemes based on numerology, geometry, fixed mapping, statistical characteristics and chemical attributes of nucleotides have been proposed in recent decades. Such coding measure schemes lack the biologically meaningful aspects of nucleotide data and hence do not significantly discriminate coding regions from non-coding regions. This paper presents a novel fuzzy semantic similarity measure (FSSM) coding scheme centering on FSSM codons׳ clustering and genetic code context of nucleotides. Certain natural characteristics of nucleotides i.e. appearance as a unique combination of triplets, preserving special structure and occurrence, and ability to own and share density distributions in codons have been exploited in FSSM. The nucleotides׳ fuzzy behaviors, semantic similarities and defuzzification based on the center of gravity of nucleotides revealed a strong correlation between nucleotides in codons. The proposed FSSM coding scheme attains a significant enhancement in coding regions identification i.e. 36-133% as compared to other existing coding measure schemes tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Uncovering highly obfuscated plagiarism cases using fuzzy semantic-based similarity model

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Salha M. Alzahrani

2015-07-01

Full Text Available Highly obfuscated plagiarism cases contain unseen and obfuscated texts, which pose difficulties when using existing plagiarism detection methods. A fuzzy semantic-based similarity model for uncovering obfuscated plagiarism is presented and compared with five state-of-the-art baselines. Semantic relatedness between words is studied based on the part-of-speech (POS tags and WordNet-based similarity measures. Fuzzy-based rules are introduced to assess the semantic distance between source and suspicious texts of short lengths, which implement the semantic relatedness between words as a membership function to a fuzzy set. In order to minimize the number of false positives and false negatives, a learning method that combines a permission threshold and a variation threshold is used to decide true plagiarism cases. The proposed model and the baselines are evaluated on 99,033 ground-truth annotated cases extracted from different datasets, including 11,621 (11.7% handmade paraphrases, 54,815 (55.4% artificial plagiarism cases, and 32,578 (32.9% plagiarism-free cases. We conduct extensive experimental verifications, including the study of the effects of different segmentations schemes and parameter settings. Results are assessed using precision, recall, F-measure and granularity on stratified 10-fold cross-validation data. The statistical analysis using paired t-tests shows that the proposed approach is statistically significant in comparison with the baselines, which demonstrates the competence of fuzzy semantic-based model to detect plagiarism cases beyond the literal plagiarism. Additionally, the analysis of variance (ANOVA statistical test shows the effectiveness of different segmentation schemes used with the proposed approach.

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

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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.

Combined semantic and similarity search in medical image databases

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Seifert, Sascha; Thoma, Marisa; Stegmaier, Florian; Hammon, Matthias; Kramer, Martin; Huber, Martin; Kriegel, Hans-Peter; Cavallaro, Alexander; Comaniciu, Dorin

2011-03-01

The current diagnostic process at hospitals is mainly based on reviewing and comparing images coming from multiple time points and modalities in order to monitor disease progression over a period of time. However, for ambiguous cases the radiologist deeply relies on reference literature or second opinion. Although there is a vast amount of acquired images stored in PACS systems which could be reused for decision support, these data sets suffer from weak search capabilities. Thus, we present a search methodology which enables the physician to fulfill intelligent search scenarios on medical image databases combining ontology-based semantic and appearance-based similarity search. It enabled the elimination of 12% of the top ten hits which would arise without taking the semantic context into account.

GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology

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Caniza, Horacio; Romero, Alfonso E.; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

2014-01-01

Summary: We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve...

The next generation of similarity measures that fully explore the semantics in biomedical ontologies.

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Couto, Francisco M; Pinto, H Sofia

2013-10-01

There is a prominent trend to augment and improve the formality of biomedical ontologies. For example, this is shown by the current effort on adding description logic axioms, such as disjointness. One of the key ontology applications that can take advantage of this effort is the conceptual (functional) similarity measurement. The presence of description logic axioms in biomedical ontologies make the current structural or extensional approaches weaker and further away from providing sound semantics-based similarity measures. Although beneficial in small ontologies, the exploration of description logic axioms by semantics-based similarity measures is computational expensive. This limitation is critical for biomedical ontologies that normally contain thousands of concepts. Thus in the process of gaining their rightful place, biomedical functional similarity measures have to take the journey of finding how this rich and powerful knowledge can be fully explored while keeping feasible computational costs. This manuscript aims at promoting and guiding the development of compelling tools that deliver what the biomedical community will require in a near future: a next-generation of biomedical similarity measures that efficiently and fully explore the semantics present in biomedical ontologies.

The Influence of Label Co-occurrence and Semantic Similarity on Children’s Inductive Generalization

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Bryan J Matlen

2015-08-01

Full Text Available Semantically-similar labels that co-occur in child-directed speech (e.g., bunny-rabbit are more likely to promote inductive generalization in preschoolers than non-co-occurring labels (e.g., lamb-sheep. However, it remains unclear whether this effect stems from co-occurrence or other factors, and how co-occurrence contributes to generalization. To address these issues, preschoolers were exposed to a stream of semantically-similar labels that don’t co-occur in natural language, but were arranged to co-occur in the experimental setting. In Experiment 1, children exposed to the co-occurring stream were more likely to make category-consistent inferences than children in two control conditions. Experiment 2 replicated this effect and provided evidence that co-occurrence training influenced generalization only when the trained labels were categorically-similar. These findings suggest that both co-occurrence information and semantic representations contribute to preschool-age children’s inductive generalization. The findings are discussed in relation to the developmental accounts of inductive generalization.

Enhancement of chemical entity identification in text using semantic similarity validation.

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Tiago Grego

Full Text Available With the amount of chemical data being produced and reported in the literature growing at a fast pace, it is increasingly important to efficiently retrieve this information. To tackle this issue text mining tools have been applied, but despite their good performance they still provide many errors that we believe can be filtered by using semantic similarity. Thus, this paper proposes a novel method that receives the results of chemical entity identification systems, such as Whatizit, and exploits the semantic relationships in ChEBI to measure the similarity between the entities found in the text. The method assigns a single validation score to each entity based on its similarities with the other entities also identified in the text. Then, by using a given threshold, the method selects a set of validated entities and a set of outlier entities. We evaluated our method using the results of two state-of-the-art chemical entity identification tools, three semantic similarity measures and two text window sizes. The method was able to increase precision without filtering a significant number of correctly identified entities. This means that the method can effectively discriminate the correctly identified chemical entities, while discarding a significant number of identification errors. For example, selecting a validation set with 75% of all identified entities, we were able to increase the precision by 28% for one of the chemical entity identification tools (Whatizit, maintaining in that subset 97% the correctly identified entities. Our method can be directly used as an add-on by any state-of-the-art entity identification tool that provides mappings to a database, in order to improve their results. The proposed method is included in a freely accessible web tool at www.lasige.di.fc.ul.pt/webtools/ice/.

Evaluation and Classification of Syntax Usage in Determining Short-Text Semantic Similarity

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V. Batanović

2014-06-01

Full Text Available This paper outlines and categorizes ways of using syntactic information in a number of algorithms for determining the semantic similarity of short texts. We consider the use of word order information, part-of-speech tagging, parsing and semantic role labeling. We analyze and evaluate the effects of syntax usage on algorithm performance by utilizing the results of a paraphrase detection test on the Microsoft Research Paraphrase Corpus. We also propose a new classification of algorithms based on their applicability to languages with scarce natural language processing tools.

Cloud based automated framework for semantic rich ontology construction and similarity computation for E-health applications

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T. MuthamilSelvan

Full Text Available Ontology structure, a core of semantic web is an excellent tool for knowledge representation and semantic visualization. Moreover, knowledge reuse is made possible through similarity measure estimation between two ontologies, threshold estimation and use of simple if-then rules for checking relevancy and irrelevancy measures. Reduced semantic representations of the ontology provide reduced knowledge visualization which is critical especially for e-health data processing and analysis. This usually occurs due to the presence of implicit knowledge and polymorphic objects and can be made semantically rich through the construction by resolving this implicit knowledge occurring in the form of non-dominant words and conditional dependence actions. This paper presents the working of the automated framework for the construction of semantic rich ontology structures and store in the repository. This construction uses dyadic deontic logic based Graph Derivation Representation in order to construct semantically rich ontologies. Moreover, in order to retrieve a set of relevant documents in response to the cloud user document, the degree of similarity between two ontologies is estimated using the traditional cosine similarity measure and simple if-then rules are used to determine the number of relevant documents and obtain such document's metadata for further processing. These working modules will be extremely beneficial to the authenticated cloud users for document retrieval, information extraction and domain dictionary construction which are especially used for e-health applications. The proposed framework is implemented using diabetes dataset and the effectiveness of the experimental results is high when compared to other Graph Derivation Representation methods. The graphical results shown in the paper is an added visualization for viewing the performance of the proposed framework. Keywords: Ontology, Implicit knowledge, Conditional dependence, Graph

Sherlock: A Semi-automatic Framework for Quiz Generation Using a Hybrid Semantic Similarity Measure.

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Lin, Chenghua; Liu, Dong; Pang, Wei; Wang, Zhe

In this paper, we present a semi-automatic system (Sherlock) for quiz generation using linked data and textual descriptions of RDF resources. Sherlock is distinguished from existing quiz generation systems in its generic framework for domain-independent quiz generation as well as in the ability of controlling the difficulty level of the generated quizzes. Difficulty scaling is non-trivial, and it is fundamentally related to cognitive science. We approach the problem with a new angle by perceiving the level of knowledge difficulty as a similarity measure problem and propose a novel hybrid semantic similarity measure using linked data. Extensive experiments show that the proposed semantic similarity measure outperforms four strong baselines with more than 47 % gain in clustering accuracy. In addition, we discovered in the human quiz test that the model accuracy indeed shows a strong correlation with the pairwise quiz similarity.

Semantic content-based recommendations using semantic graphs.

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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.

A grammar-based semantic similarity algorithm for natural language sentences.

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Lee, Ming Che; Chang, Jia Wei; Hsieh, Tung Cheng

2014-01-01

This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to "artificial language", such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches, such as vector models, LSA, HAL, or even the ontology-based approaches that extend to include concept similarity comparison instead of cooccurrence terms/words, may not always determine the perfect matching while there is no obvious relation or concept overlap between two natural language sentences. This paper proposes a sentence similarity algorithm that takes advantage of corpus-based ontology and grammatical rules to overcome the addressed problems. Experiments on two famous benchmarks demonstrate that the proposed algorithm has a significant performance improvement in sentences/short-texts with arbitrary syntax and structure.

GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology.

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Caniza, Horacio; Romero, Alfonso E; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

2014-08-01

We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve the accuracy of similarity measures. GOssTo is very fast, easy to use, and it allows the calculation of similarities on a genomic scale in a few minutes on a regular desktop machine. alberto@cs.rhul.ac.uk GOssTo is available both as a stand-alone application running on GNU/Linux, Windows and MacOS from www.paccanarolab.org/gossto and as a web application from www.paccanarolab.org/gosstoweb. The stand-alone application features a simple and concise command line interface for easy integration into high-throughput data processing pipelines. © The Author 2014. Published by Oxford University Press.

Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

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Zhang, Shu-Bo; Tang, Qiang-Rong

2016-07-21

Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using ontology-based semantic similarity to facilitate the article screening process for systematic reviews.

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Ji, Xiaonan; Ritter, Alan; Yen, Po-Yin

2017-05-01

Systematic Reviews (SRs) are utilized to summarize evidence from high quality studies and are considered the preferred source of evidence-based practice (EBP). However, conducting SRs can be time and labor intensive due to the high cost of article screening. In previous studies, we demonstrated utilizing established (lexical) article relationships to facilitate the identification of relevant articles in an efficient and effective manner. Here we propose to enhance article relationships with background semantic knowledge derived from Unified Medical Language System (UMLS) concepts and ontologies. We developed a pipelined semantic concepts representation process to represent articles from an SR into an optimized and enriched semantic space of UMLS concepts. Throughout the process, we leveraged concepts and concept relations encoded in biomedical ontologies (SNOMED-CT and MeSH) within the UMLS framework to prompt concept features of each article. Article relationships (similarities) were established and represented as a semantic article network, which was readily applied to assist with the article screening process. We incorporated the concept of active learning to simulate an interactive article recommendation process, and evaluated the performance on 15 completed SRs. We used work saved over sampling at 95% recall (WSS95) as the performance measure. We compared the WSS95 performance of our ontology-based semantic approach to existing lexical feature approaches and corpus-based semantic approaches, and found that we had better WSS95 in most SRs. We also had the highest average WSS95 of 43.81% and the highest total WSS95 of 657.18%. We demonstrated using ontology-based semantics to facilitate the identification of relevant articles for SRs. Effective concepts and concept relations derived from UMLS ontologies can be utilized to establish article semantic relationships. Our approach provided a promising performance and can easily apply to any SR topics in the

A Grammar-Based Semantic Similarity Algorithm for Natural Language Sentences

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Chang, Jia Wei; Hsieh, Tung Cheng

2014-01-01

This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to “artificial language”, such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches, such as vector models, LSA, HAL, or even the ontology-based approaches that extend to include concept similarity comparison instead of cooccurrence terms/words, may not always determine the perfect matching while there is no obvious relation or concept overlap between two natural language sentences. This paper proposes a sentence similarity algorithm that takes advantage of corpus-based ontology and grammatical rules to overcome the addressed problems. Experiments on two famous benchmarks demonstrate that the proposed algorithm has a significant performance improvement in sentences/short-texts with arbitrary syntax and structure. PMID:24982952

A Grammar-Based Semantic Similarity Algorithm for Natural Language Sentences

Directory of Open Access Journals (Sweden)

Ming Che Lee

2014-01-01

Full Text Available This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to “artificial language”, such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches, such as vector models, LSA, HAL, or even the ontology-based approaches that extend to include concept similarity comparison instead of cooccurrence terms/words, may not always determine the perfect matching while there is no obvious relation or concept overlap between two natural language sentences. This paper proposes a sentence similarity algorithm that takes advantage of corpus-based ontology and grammatical rules to overcome the addressed problems. Experiments on two famous benchmarks demonstrate that the proposed algorithm has a significant performance improvement in sentences/short-texts with arbitrary syntax and structure.

MEASURING THE PERFORMANCE OF SIMILARITY PROPAGATION IN AN SEMANTIC SEARCH ENGINE

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S. K. Jayanthi

2013-10-01

Full Text Available In the current scenario, web page result personalization is playing a vital role. Nearly 80 % of the users expect the best results in the first page itself without having any persistence to browse longer in URL mode. This research work focuses on two main themes: Semantic web search through online and Domain based search through offline. The first part is to find an effective method which allows grouping similar results together using BookShelf Data Structure and organizing the various clusters. The second one is focused on the academic domain based search through offline. This paper focuses on finding documents which are similar and how Vector space can be used to solve it. So more weightage is given for the principles and working methodology of similarity propagation. Cosine similarity measure is used for finding the relevancy among the documents.

SemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional association.

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Liang Cheng

Full Text Available Measuring similarity between diseases plays an important role in disease-related molecular function research. Functional associations between disease-related genes and semantic associations between diseases are often used to identify pairs of similar diseases from different perspectives. Currently, it is still a challenge to exploit both of them to calculate disease similarity. Therefore, a new method (SemFunSim that integrates semantic and functional association is proposed to address the issue.SemFunSim is designed as follows. First of all, FunSim (Functional similarity is proposed to calculate disease similarity using disease-related gene sets in a weighted network of human gene function. Next, SemSim (Semantic Similarity is devised to calculate disease similarity using the relationship between two diseases from Disease Ontology. Finally, FunSim and SemSim are integrated to measure disease similarity.The high average AUC (area under the receiver operating characteristic curve (96.37% shows that SemFunSim achieves a high true positive rate and a low false positive rate. 79 of the top 100 pairs of similar diseases identified by SemFunSim are annotated in the Comparative Toxicogenomics Database (CTD as being targeted by the same therapeutic compounds, while other methods we compared could identify 35 or less such pairs among the top 100. Moreover, when using our method on diseases without annotated compounds in CTD, we could confirm many of our predicted candidate compounds from literature. This indicates that SemFunSim is an effective method for drug repositioning.

Prioritization of candidate disease genes by combining topological similarity and semantic similarity.

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Liu, Bin; Jin, Min; Zeng, Pan

2015-10-01

The identification of gene-phenotype relationships is very important for the treatment of human diseases. Studies have shown that genes causing the same or similar phenotypes tend to interact with each other in a protein-protein interaction (PPI) network. Thus, many identification methods based on the PPI network model have achieved good results. However, in the PPI network, some interactions between the proteins encoded by candidate gene and the proteins encoded by known disease genes are very weak. Therefore, some studies have combined the PPI network with other genomic information and reported good predictive performances. However, we believe that the results could be further improved. In this paper, we propose a new method that uses the semantic similarity between the candidate gene and known disease genes to set the initial probability vector of a random walk with a restart algorithm in a human PPI network. The effectiveness of our method was demonstrated by leave-one-out cross-validation, and the experimental results indicated that our method outperformed other methods. Additionally, our method can predict new causative genes of multifactor diseases, including Parkinson's disease, breast cancer and obesity. The top predictions were good and consistent with the findings in the literature, which further illustrates the effectiveness of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

Trends in Modern Exception Handling

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Marcin Kuta

2003-01-01

Full Text Available Exception handling is nowadays a necessary component of error proof information systems. The paper presents overview of techniques and models of exception handling, problems connected with them and potential solutions. The aspects of implementation of propagation mechanisms and exception handling, their effect on semantics and general program efficiency are also taken into account. Presented mechanisms were adopted to modern programming languages. Considering design area, formal methods and formal verification of program properties we can notice exception handling mechanisms are weakly present what makes a field for future research.

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

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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.

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...

Semantic Enrichment of Movement Behavior with Foursquare--A Visual Analytics Approach.

Science.gov (United States)

Krueger, Robert; Thom, Dennis; Ertl, Thomas

2015-08-01

In recent years, many approaches have been developed that efficiently and effectively visualize movement data, e.g., by providing suitable aggregation strategies to reduce visual clutter. Analysts can use them to identify distinct movement patterns, such as trajectories with similar direction, form, length, and speed. However, less effort has been spent on finding the semantics behind movements, i.e. why somebody or something is moving. This can be of great value for different applications, such as product usage and consumer analysis, to better understand urban dynamics, and to improve situational awareness. Unfortunately, semantic information often gets lost when data is recorded. Thus, we suggest to enrich trajectory data with POI information using social media services and show how semantic insights can be gained. Furthermore, we show how to handle semantic uncertainties in time and space, which result from noisy, unprecise, and missing data, by introducing a POI decision model in combination with highly interactive visualizations. Finally, we evaluate our approach with two case studies on a large electric scooter data set and test our model on data with known ground truth.

Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.

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Masino, Aaron J; Dechene, Elizabeth T; Dulik, Matthew C; Wilkens, Alisha; Spinner, Nancy B; Krantz, Ian D; Pennington, Jeffrey W; Robinson, Peter N; White, Peter S

2014-07-21

Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content. Model validation was performed via simulation and with clinical data. We simulated 33 Mendelian diseases with 100 patients per disease. We modeled clinical conditions by adding noise and imprecision, i.e. phenotypic terms unrelated to the disease and terms less specific than the actual disease terms. We ranked the causative gene against all 2488 HPO annotated genes. The median causative gene rank was 1 for the optimal and noise cases, 12 for the imprecision case, and 60 for the imprecision with noise case. Additionally, we examined a clinical cohort of subjects with hearing impairment. The disease gene median rank was 22. However, when also considering the patient's exome data and filtering non-exomic and common variants, the median rank improved to 3. Semantic similarity can rank a causative gene highly within a gene list relative to patient phenotype characteristics, provided that imprecision is mitigated. The clinical case results suggest that phenotype rank combined with variant analysis provides significant improvement over the individual approaches. We expect that this combined prioritization approach may increase accuracy and decrease effort for

Toward an enhanced Arabic text classification using cosine similarity and Latent Semantic

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Fawaz S. Al-Anzi

2017-04-01

Full Text Available Cosine similarity is one of the most popular distance measures in text classification problems. In this paper, we used this important measure to investigate the performance of Arabic language text classification. For textual features, vector space model (VSM is generally used as a model to represent textual information as numerical vectors. However, Latent Semantic Indexing (LSI is a better textual representation technique as it maintains semantic information between the words. Hence, we used the singular value decomposition (SVD method to extract textual features based on LSI. In our experiments, we conducted comparison between some of the well-known classification methods such as Naïve Bayes, k-Nearest Neighbors, Neural Network, Random Forest, Support Vector Machine, and classification tree. We used a corpus that contains 4,000 documents of ten topics (400 document for each topic. The corpus contains 2,127,197 words with about 139,168 unique words. The testing set contains 400 documents, 40 documents for each topics. As a weighing scheme, we used Term Frequency.Inverse Document Frequency (TF.IDF. This study reveals that the classification methods that use LSI features significantly outperform the TF.IDF-based methods. It also reveals that k-Nearest Neighbors (based on cosine measure and support vector machine are the best performing classifiers.

Semantic similarity-based alignment between clinical archetypes and SNOMED CT: an application to observations.

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Meizoso García, María; Iglesias Allones, José Luis; Martínez Hernández, Diego; Taboada Iglesias, María Jesús

2012-08-01

One of the main challenges of eHealth is semantic interoperability of health systems. But, this will only be possible if the capture, representation and access of patient data is standardized. Clinical data models, such as OpenEHR Archetypes, define data structures that are agreed by experts to ensure the accuracy of health information. In addition, they provide an option to normalize clinical data by means of binding terms used in the model definition to standard medical vocabularies. Nevertheless, the effort needed to establish the association between archetype terms and standard terminology concepts is considerable. Therefore, the purpose of this study is to provide an automated approach to bind OpenEHR archetypes terms to the external terminology SNOMED CT, with the capability to do it at a semantic level. This research uses lexical techniques and external terminological tools in combination with context-based techniques, which use information about structural and semantic proximity to identify similarities between terms and so, to find alignments between them. The proposed approach exploits both the structural context of archetypes and the terminology context, in which concepts are logically defined through the relationships (hierarchical and definitional) to other concepts. A set of 25 OBSERVATION archetypes with 477 bound terms was used to test the method. Of these, 342 terms (74.6%) were linked with 96.1% precision, 71.7% recall and 1.23 SNOMED CT concepts on average for each mapping. It has been detected that about one third of the archetype clinical information is grouped logically. Context-based techniques take advantage of this to increase the recall and to validate a 30.4% of the bindings produced by lexical techniques. This research shows that it is possible to automatically map archetype terms to a standard terminology with a high precision and recall, with the help of appropriate contextual and semantic information of both models. Moreover, the

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...

Web service composition: a semantic web and automated planning technique application

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Jaime Alberto Guzmán Luna

2008-09-01

Full Text Available This article proposes applying semantic web and artificial intelligence planning techniques to a web services composition model dealing with problems of ambiguity in web service description and handling incomplete web information. The model uses an OWL-S services and implements a planning technique which handles open world semantics in its reasoning process to resolve these problems. This resulted in a web services composition system incorporating a module for interpreting OWL-S services and converting them into a planning problem in PDDL (a planning module handling incomplete information and an execution service module concurrently interacting with the planner for executing each composition plan service.

Interpreting semantic clustering effects in free recall.

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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.

LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

Energy Technology Data Exchange (ETDEWEB)

VERSPOOR, KARIN [Los Alamos National Laboratory; LIN, SHOU-DE [Los Alamos National Laboratory

2007-01-29

An N-gram language model aims at capturing statistical syntactic word order information from corpora. Although the concept of language models has been applied extensively to handle a variety of NLP problems with reasonable success, the standard model does not incorporate semantic information, and consequently limits its applicability to semantic problems such as word sense disambiguation. We propose a framework that integrates semantic information into the language model schema, allowing a system to exploit both syntactic and semantic information to address NLP problems. Furthermore, acknowledging the limited availability of semantically annotated data, we discuss how the proposed model can be learned without annotated training examples. Finally, we report on a case study showing how the semantics-enhanced language model can be applied to unsupervised word sense disambiguation with promising results.

SemVisM: semantic visualizer for medical image

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Landaeta, Luis; La Cruz, Alexandra; Baranya, Alexander; Vidal, María.-Esther

2015-01-01

SemVisM is a toolbox that combines medical informatics and computer graphics tools for reducing the semantic gap between low-level features and high-level semantic concepts/terms in the images. This paper presents a novel strategy for visualizing medical data annotated semantically, combining rendering techniques, and segmentation algorithms. SemVisM comprises two main components: i) AMORE (A Modest vOlume REgister) to handle input data (RAW, DAT or DICOM) and to initially annotate the images using terms defined on medical ontologies (e.g., MesH, FMA or RadLex), and ii) VOLPROB (VOlume PRObability Builder) for generating the annotated volumetric data containing the classified voxels that belong to a particular tissue. SemVisM is built on top of the semantic visualizer ANISE.1

Semantic guidance of eye movements in real-world scenes.

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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.

Semantic Coherence Facilitates Distributional Learning.

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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.

Effects of perceptual similarity but not semantic association on false recognition in aging

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Kayleigh Burnside

2017-12-01

Full Text Available This study investigated semantic and perceptual influences on false recognition in older and young adults in a variant on the Deese-Roediger-McDermott paradigm. In two experiments, participants encoded intermixed sets of semantically associated words, and sets of unrelated words. Each set was presented in a shared distinctive font. Older adults were no more likely to falsely recognize semantically associated lure words compared to unrelated lures also presented in studied fonts. However, they showed an increase in false recognition of lures which were related to studied items only by a shared font. This increased false recognition was associated with recollective experience. The data show that older adults do not always rely more on prior knowledge in episodic memory tasks. They converge with other findings suggesting that older adults may also be more prone to perceptually-driven errors.

Toward Better Mapping between Regulations and Operations of Enterprises Using Vocabularies and Semantic Similarity

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Sagar Sunkle

2015-12-01

Full Text Available Industry governance, risk, and compliance (GRC solutions stand to gain from various analyses offered by formal compliance checking approaches. Such adoption is made difficult by the fact that most formal approaches assume that a mapping between concepts of regulations and models of operational specifics exists. Industry solutions offer tagging mechanisms to map regulations to operational specifics; however, they are mostly semi-formal in nature and tend to rely extensively on experts. We propose to use Semantics of Business Vocabularies and Rules along with similarity measures to create an explicit mapping between concepts of regulations and models of operational specifics of the enterprise. We believe that our work-in-progress takes a step toward adapting and leveraging formal compliance checking approaches in industry GRC solutions.

Arabic web pages clustering and annotation using semantic class features

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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.

Fast Distributed Dynamics of Semantic Networks via Social Media

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Facundo Carrillo

2015-01-01

Full Text Available We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS, based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the distributed structure of semantic relationships across the entire lexicon. Using TSS, we measured the evolution of a concept and its movement along the semantic neighborhood, driven by specific news/events. Finally, we showed that particular events may trigger a temporary reorganization of elements in the semantic network.

PSG: Peer-to-Peer semantic grid framework architecture

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Amira Soliman

2011-07-01

Full Text Available The grid vision, of sharing diverse resources in a flexible, coordinated and secure manner, strongly depends on metadata. Currently, grid metadata is generated and used in an ad-hoc fashion, much of it buried in the grid middleware code libraries and database schemas. This ad-hoc expression and use of metadata causes chronic dependency on human intervention during the operation of grid machinery. Therefore, the Semantic Grid is emerged as an extension of the grid in which rich resource metadata is exposed and handled explicitly, and shared and managed via grid protocols. The layering of an explicit semantic infrastructure over the grid infrastructure potentially leads to increase interoperability and flexibility. In this paper, we present PSG framework architecture that offers semantic-based grid services. PSG architecture allows the explicit use of semantics and defining the associated grid services. PSG architecture is originated from the integration of Peer-to-Peer (P2P computing with semantics and agents. Ontologies are used in annotating each grid component, developing users/nodes profiles and organizing framework agents. While, P2P is responsible for organizing and coordinating the grid nodes and resources.

Psycholinguistic measures for German verb pairs: Semantic transparency, semantic relatedness, verb family size, and age of reading acquisition.

Science.gov (United States)

Smolka, Eva; Eulitz, Carsten

2018-06-18

A central issue in visual and spoken word recognition is the lexical representation of complex words-in particular, whether the lexical representation of complex words depends on semantic transparency: Is a complex verb like understand lexically represented as a whole word or via its base stand, given that its meaning is not transparent from the meanings of its parts? To study this issue, a number of stimulus characteristics are of interest that are not yet available in public databases of German. This article provides semantic association ratings, lexical paraphrases, and vector-based similarity measures for German verbs, measuring (a) the semantic transparency between 1,259 complex verbs and their bases, (b) the semantic relatedness between 1,109 verb pairs with 432 different bases, and (c) the vector-based similarity measures of 846 verb pairs. Additionally, we include the verb regularity of all verbs and two counts of verb family size for 184 base verbs, as well as estimates of age of acquisition and age of reading for 200 verbs. Together with lemma and type frequencies from public lexical databases, all measures can be downloaded along with this article. Statistical analyses indicate that verb family size, morphological complexity, frequency, and verb regularity affect the semantic transparency and relatedness ratings as well as the age of acquisition estimates, indicating that these are relevant variables in psycholinguistic experiments. Although lexical paraphrases, vector-based similarity measures, and semantic association ratings may deliver complementary information, the interrater reliability of the semantic association ratings for each verb pair provides valuable information when selecting stimuli for psycholinguistic experiments.

On proving confluence modulo equivalence for Constraint Handling Rules

DEFF Research Database (Denmark)

Christiansen, Henning; Kirkeby, Maja Hanne

2017-01-01

-logical built-in predicates such as var/1 and incomplete ones such as is/2, that are ignored in previous work on confluence. To this end, a new operational semantics for CHR is developed which includes such predicates. In addition, this semantics differs from earlier approaches by its simplicity without loss......Previous results on proving confluence for Constraint Handling Rules are extended in two ways in order to allow a larger and more realistic class of CHR programs to be considered confluent. Firstly, we introduce the relaxed notion of confluence modulo equivalence into the context of CHR: while...

Semantic Data Matching: Principles and Performance

Science.gov (United States)

Deaton, Russell; Doan, Thao; Schweiger, Tom

Automated and real-time management of customer relationships requires robust and intelligent data matching across widespread and diverse data sources. Simple string matching algorithms, such as dynamic programming, can handle typographical errors in the data, but are less able to match records that require contextual and experiential knowledge. Latent Semantic Indexing (LSI) (Berry et al. ; Deerwester et al. is a machine intelligence technique that can match data based upon higher order structure, and is able to handle difficult problems, such as words that have different meanings but the same spelling, are synonymous, or have multiple meanings. Essentially, the technique matches records based upon context, or mathematically quantifying when terms occur in the same record.

A Denotational Semantics for Communicating Unstructured Code

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Nils Jähnig

2015-03-01

Full Text Available An important property of programming language semantics is that they should be compositional. However, unstructured low-level code contains goto-like commands making it hard to define a semantics that is compositional. In this paper, we follow the ideas of Saabas and Uustalu to structure low-level code. This gives us the possibility to define a compositional denotational semantics based on least fixed points to allow for the use of inductive verification methods. We capture the semantics of communication using finite traces similar to the denotations of CSP. In addition, we examine properties of this semantics and give an example that demonstrates reasoning about communication and jumps. With this semantics, we lay the foundations for a proof calculus that captures both, the semantics of unstructured low-level code and communication.

A Semantics for Distributed Execution of Statemate

DEFF Research Database (Denmark)

Fränzle, Martin; Niehaus, Jürgen; Metzner, Alexander

2003-01-01

We present a semantics for the statechart variant implemented in the Statemate product of i-Logix. Our semantics enables distributed code generation for Statemate models in the context of rapid prototyping for embedded control applications. We argue that it seems impossible to efficiently generate......, the changes made regarding the interaction of distributed model parts are similar to the interaction between the model and its environment in the original semantics, thus giving designers a familiar execution model. The semantics has been implemented in Grace, a framework for rapid prototyping code generation...... distributed code using the original Statemate semantics. The new, distributed semantics has the advantages that, first, it enables the generation of efficient distributed code, second, it preserves many aspects of the original semantics for those parts of a model that are not distributed, and third...

Lung Cancer Signature Biomarkers: tissue specific semantic similarity based clustering of Digital Differential Display (DDD data

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Srivastava Mousami

2012-11-01

Full Text Available Abstract Background The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal and disease (cancer sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Results Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95 identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4. Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1, chemotherapy/drug resistance biomarkers (panel 2, hypoxia regulated biomarkers (panel 3 and lung extra cellular matrix biomarkers (panel 4. Conclusions Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3, HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1

Semantical Markov Logic Network for Distributed Reasoning in Cyber-Physical Systems

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Abdul-Wahid Mohammed

2017-01-01

Full Text Available The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home.

Conceptual similarity effects on working memory in sentence contexts: testing a theory of anaphora.

Science.gov (United States)

Cowles, H Wind; Garnham, Alan; Simner, Julia

2010-06-01

The degree of semantic similarity between an anaphoric noun phrase (e.g., the bird) and its antecedent (e.g., a robin) is known to affect the anaphor resolution process, but the mechanisms that underlie this effect are not known. One proposal (Almor, 1999) is that semantic similarity triggers interference effects in working memory and makes two crucial assumptions: First, semantic similarity impairs working memory just as phonological similarity does (e.g., Baddeley, 1992), and, second, this impairment interferes with processes of sentence comprehension. We tested these assumptions in two experiments that compared recall accuracy between phonologically similar, semantically similar, and control words in sentence contexts. Our results do not provide support for Almor's claims: Phonological overlap decreased recall accuracy in sentence contexts, but semantic similarity did not. These results shed doubt on the idea that semantic interference in working memory is an underlying mechanism in anaphor resolution.

Preserved cumulative semantic interference despite amnesia

Directory of Open Access Journals (Sweden)

Gary Michael Oppenheim

2015-05-01

As predicted by Oppenheim et al’s (2010 implicit incremental learning account, WRP’s BCN RTs demonstrated strong (and significant repetition priming and semantic blocking effects (Figure 1. Similar to typical results from neurally intact undergraduates, WRP took longer to name pictures presented in semantically homogeneous blocks than in heterogeneous blocks, an effect that increased with each cycle. This result challenges accounts that ascribe cumulative semantic interference in this task to explicit memory mechanisms, instead suggesting that the effect has the sort of implicit learning bases that are typically spared in hippocampal amnesia.

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.

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.

SoyBase Simple Semantic Web Architecture and Protocol (SSWAP) Services

Science.gov (United States)

Semantic web technologies offer the potential to link internet resources and data by shared concepts without having to rely on absolute lexical matches. Thus two web sites or web resources which are concerned with similar data types could be identified based on similar semantics. In the biological...

29 CFR 1917.73 - Terminal facilities handling menhaden and similar species of fish (see also § 1917.2, definition...

Science.gov (United States)

2010-07-01

... of fish (see also § 1917.2, definition of hazardous cargo, material, substance or atmosphere). 1917... facilities handling menhaden and similar species of fish (see also § 1917.2, definition of hazardous cargo... respiratory protective equipment consisting of supplied-air respirators or self-contained breathing apparatus...

Ontology Matching with Semantic Verification.

Science.gov (United States)

Jean-Mary, Yves R; Shironoshita, E Patrick; Kabuka, Mansur R

2009-09-01

ASMOV (Automated Semantic Matching of Ontologies with Verification) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies.

In the pursuit of a semantic similarity metric based on UMLS annotations for articles in PubMed Central Open Access.

Science.gov (United States)

Garcia Castro, Leyla Jael; Berlanga, Rafael; Garcia, Alexander

2015-10-01

Although full-text articles are provided by the publishers in electronic formats, it remains a challenge to find related work beyond the title and abstract context. Identifying related articles based on their abstract is indeed a good starting point; this process is straightforward and does not consume as many resources as full-text based similarity would require. However, further analyses may require in-depth understanding of the full content. Two articles with highly related abstracts can be substantially different regarding the full content. How similarity differs when considering title-and-abstract versus full-text and which semantic similarity metric provides better results when dealing with full-text articles are the main issues addressed in this manuscript. We have benchmarked three similarity metrics - BM25, PMRA, and Cosine, in order to determine which one performs best when using concept-based annotations on full-text documents. We also evaluated variations in similarity values based on title-and-abstract against those relying on full-text. Our test dataset comprises the Genomics track article collection from the 2005 Text Retrieval Conference. Initially, we used an entity recognition software to semantically annotate titles and abstracts as well as full-text with concepts defined in the Unified Medical Language System (UMLS®). For each article, we created a document profile, i.e., a set of identified concepts, term frequency, and inverse document frequency; we then applied various similarity metrics to those document profiles. We considered correlation, precision, recall, and F1 in order to determine which similarity metric performs best with concept-based annotations. For those full-text articles available in PubMed Central Open Access (PMC-OA), we also performed dispersion analyses in order to understand how similarity varies when considering full-text articles. We have found that the PubMed Related Articles similarity metric is the most suitable for

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...

Semantics and pragmatics.

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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.

Neural pattern similarity underlies the mnemonic advantages for living words.

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Xiao, Xiaoqian; Dong, Qi; Chen, Chuansheng; Xue, Gui

2016-06-01

It has been consistently shown that words representing living things are better remembered than words representing nonliving things, yet the underlying cognitive and neural mechanisms have not been clearly elucidated. The present study used both univariate and multivariate pattern analyses to examine the hypotheses that living words are better remembered because (1) they draw more attention and/or (2) they share more overlapping semantic features. Subjects were asked to study a list of living and nonliving words during a semantic judgment task. An unexpected recognition test was administered 30 min later. We found that subjects recognized significantly more living words than nonliving words. Results supported the overlapping semantic feature hypothesis by showing that (a) semantic ratings showed greater semantic similarity for living words than for nonliving words, (b) there was also significantly greater neural global pattern similarity (nGPS) for living words than for nonliving words in the posterior portion of left parahippocampus (LpPHG), (c) the nGPS in the LpPHG reflected the rated semantic similarity, and also mediated the memory differences between two semantic categories, and (d) greater univariate activation was found for living words than for nonliving words in the left hippocampus (LHIP), which mediated the better memory performance for living words and might reflect greater semantic context binding. In contrast, although living words were processed faster and elicited a stronger activity in the dorsal attention network, these differences did not mediate the animacy effect in memory. Taken together, our results provide strong support to the overlapping semantic features hypothesis, and emphasize the important role of semantic organization in episodic memory encoding. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biomedical semantics in the Semantic Web.

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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.

Semantic representations in the temporal pole predict false memories.

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Chadwick, Martin J; Anjum, Raeesa S; Kumaran, Dharshan; Schacter, Daniel L; Spiers, Hugo J; Hassabis, Demis

2016-09-06

Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the "semantic hub" of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories.

Semantic representations in the temporal pole predict false memories

Science.gov (United States)

Chadwick, Martin J.; Anjum, Raeesa S.; Kumaran, Dharshan; Schacter, Daniel L.; Spiers, Hugo J.; Hassabis, Demis

2016-01-01

Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the “semantic hub” of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories. PMID:27551087

Semantics of immersive web through its architectural structure and graphic primitives

Directory of Open Access Journals (Sweden)

Rubén González Crespo

2010-12-01

Full Text Available Currently, practices and tools for computer-aided three-dimensional design, do not allow the semantic description of objects constructed in some cases specified notations as handling layers, or labeling of each development itself. The lack of a standard for the description of the elements represents a major drawback for using advanced three-dimensional environments such as the automation of search and construction processes that require semantic knowledge of its elements.This project proposes the development the semantic composition from the hierarchy of three-dimensional visualization of graphics primitives used to construct three-dimensional objects, taking into account the geometric composition architecture of standard 19775-1 of the International Electrotechnical Commission of the International Organization for StandardizationFor the development of semantic composition use the methodology methontology proposed by the Universidad Politécnica de Madrid, because it allows the construction of ontologies about specific domains, limiting the domain by defining classes and subclasses, relationships and the generation of instances a framework for resource description on web ontology language.

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.

Automation and semantics: the CombeChem experience

OpenAIRE

Frey, Jeremy G.

2004-01-01

Some of the experiences of the CombeChem e-Science project in relation to both automation and the need for semantics in combining modern computer science techniques and chemistry are discussed. In particular the aspects of the smart laboratory, large scale data handling and the way this impacts on the necessary database technology are discussed. In addition some of the ways in which the grid can enable greater user interaction with services such as the National Crystallography Service and imp...

The Universality of Semantic Prototypes in Spanish Lexical Availability

Directory of Open Access Journals (Sweden)

Marjana Šifrar Kalan

2016-12-01

Full Text Available The article presents the words with highest index of availability on the basis of semantic fluency tests. The conceptual stability of highly available words in various semantic categories enables them to be classified as semantic prototypes according to the theory of prototype. The aim of this article is to compare the semantic prototypes in nine semantic categories from different lexical availability studies: those carried out in Spanish as a mother tongue and Spanish as a foreign language (with Slovene, Finnish, Turkish, Chinese students and students of various other mother tongues who studied Spanish in Madrid and Salamanca. The informants who come from different countries and cultures and speak different first languages demonstrate that human beings share the same or similar categorization and universality of semantic prototypes.

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...

Phonological and semantic strategies in immediate serial recall.

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Campoy, Guillermo; Baddeley, Alan

2008-05-01

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

Latent semantic analysis.

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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.

The picture superiority effect in categorization: visual or semantic?

Science.gov (United States)

Job, R; Rumiati, R; Lotto, L

1992-09-01

Two experiments are reported whose aim was to replicate and generalize the results presented by Snodgrass and McCullough (1986) on the effect of visual similarity in the categorization process. For pictures, Snodgrass and McCullough's results were replicated because Ss took longer to discriminate elements from 2 categories when they were visually similar than when they were visually dissimilar. However, unlike Snodgrass and McCullough, an analogous increase was also observed for word stimuli. The pattern of results obtained here can be explained most parsimoniously with reference to the effect of semantic similarity, or semantic and visual relatedness, rather than to visual similarity alone.

Semantic Web-Driven LMS Architecture towards a Holistic Learning Process Model Focused on Personalization

Science.gov (United States)

Kerkiri, Tania

2010-01-01

A comprehensive presentation is here made on the modular architecture of an e-learning platform with a distinctive emphasis on content personalization, combining advantages from semantic web technology, collaborative filtering and recommendation systems. Modules of this architecture handle information about both the domain-specific didactic…

Semantator: annotating clinical narratives with semantic web ontologies.

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

2012-01-01

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

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...

Discovering Music Structure via Similarity Fusion

DEFF Research Database (Denmark)

for representing music structure is studied in a simplified scenario consisting of 4412 songs and two similarity measures among them. The results suggest that the PLSA model is a useful framework to combine different sources of information, and provides a reasonable space for song representation.......Automatic methods for music navigation and music recommendation exploit the structure in the music to carry out a meaningful exploration of the “song space”. To get a satisfactory performance from such systems, one should incorporate as much information about songs similarity as possible; however...... semantics”, in such a way that all observed similarities can be satisfactorily explained using the latent semantics. Therefore, one can think of these semantics as the real structure in music, in the sense that they can explain the observed similarities among songs. The suitability of the PLSA model...

Discovering Music Structure via Similarity Fusion

DEFF Research Database (Denmark)

Arenas-García, Jerónimo; Parrado-Hernandez, Emilio; Meng, Anders

Automatic methods for music navigation and music recommendation exploit the structure in the music to carry out a meaningful exploration of the “song space”. To get a satisfactory performance from such systems, one should incorporate as much information about songs similarity as possible; however...... semantics”, in such a way that all observed similarities can be satisfactorily explained using the latent semantics. Therefore, one can think of these semantics as the real structure in music, in the sense that they can explain the observed similarities among songs. The suitability of the PLSA model...... for representing music structure is studied in a simplified scenario consisting of 4412 songs and two similarity measures among them. The results suggest that the PLSA model is a useful framework to combine different sources of information, and provides a reasonable space for song representation....

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.

Connecting long distance: semantic distance in analogical reasoning modulates frontopolar cortex activity.

Science.gov (United States)

Green, Adam E; Kraemer, David J M; Fugelsang, Jonathan A; Gray, Jeremy R; Dunbar, Kevin N

2010-01-01

Solving problems often requires seeing new connections between concepts or events that seemed unrelated at first. Innovative solutions of this kind depend on analogical reasoning, a relational reasoning process that involves mapping similarities between concepts. Brain-based evidence has implicated the frontal pole of the brain as important for analogical mapping. Separately, cognitive research has identified semantic distance as a key characteristic of the kind of analogical mapping that can support innovation (i.e., identifying similarities across greater semantic distance reveals connections that support more innovative solutions and models). However, the neural substrates of semantically distant analogical mapping are not well understood. Here, we used functional magnetic resonance imaging (fMRI) to measure brain activity during an analogical reasoning task, in which we parametrically varied the semantic distance between the items in the analogies. Semantic distance was derived quantitatively from latent semantic analysis. Across 23 participants, activity in an a priori region of interest (ROI) in left frontopolar cortex covaried parametrically with increasing semantic distance, even after removing effects of task difficulty. This ROI was centered on a functional peak that we previously associated with analogical mapping. To our knowledge, these data represent a first empirical characterization of how the brain mediates semantically distant analogical mapping.

Exploiting semantic linkages among multiple sources for semantic information retrieval

Science.gov (United States)

Li, JianQiang; Yang, Ji-Jiang; Liu, Chunchen; Zhao, Yu; Liu, Bo; Shi, Yuliang

2014-07-01

The vision of the Semantic Web is to build a global Web of machine-readable data to be consumed by intelligent applications. As the first step to make this vision come true, the initiative of linked open data has fostered many novel applications aimed at improving data accessibility in the public Web. Comparably, the enterprise environment is so different from the public Web that most potentially usable business information originates in an unstructured form (typically in free text), which poses a challenge for the adoption of semantic technologies in the enterprise environment. Considering that the business information in a company is highly specific and centred around a set of commonly used concepts, this paper describes a pilot study to migrate the concept of linked data into the development of a domain-specific application, i.e. the vehicle repair support system. The set of commonly used concepts, including the part name of a car and the phenomenon term on the car repairing, are employed to build the linkage between data and documents distributed among different sources, leading to the fusion of documents and data across source boundaries. Then, we describe the approaches of semantic information retrieval to consume these linkages for value creation for companies. The experiments on two real-world data sets show that the proposed approaches outperform the best baseline 6.3-10.8% and 6.4-11.1% in terms of top five and top 10 precisions, respectively. We believe that our pilot study can serve as an important reference for the development of similar semantic applications in an enterprise environment.

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.

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

Semantic search during divergent thinking.

Science.gov (United States)

Hass, Richard W

2017-09-01

Divergent thinking, as a method of examining creative cognition, has not been adequately analyzed in the context of modern cognitive theories. This article casts divergent thinking responding in the context of theories of memory search. First, it was argued that divergent thinking tasks are similar to semantic fluency tasks, but are more constrained, and less well structured. Next, response time distributions from 54 participants were analyzed for temporal and semantic clustering. Participants responded to two prompts from the alternative uses test: uses for a brick and uses for a bottle, for two minutes each. Participants' cumulative response curves were negatively accelerating, in line with theories of search of associative memory. However, results of analyses of semantic and temporal clustering suggested that clustering is less evident in alternative uses responding compared to semantic fluency tasks. This suggests either that divergent thinking responding does not involve an exhaustive search through a clustered memory trace, but rather that the process is more exploratory, yielding fewer overall responses that tend to drift away from close associates of the divergent thinking prompt. Copyright © 2017 Elsevier B.V. All rights reserved.

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

Science.gov (United States)

El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

2015-11-01

Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

Semantic error patterns on the Boston Naming Test in normal aging, amnestic mild cognitive impairment, and mild Alzheimer's disease: is there semantic disruption?

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Balthazar, Marcio Luiz Figueredo; Cendes, Fernando; Damasceno, Benito Pereira

2008-11-01

Naming difficulty is common in Alzheimer's disease (AD), but the nature of this problem is not well established. The authors investigated the presence of semantic breakdown and the pattern of general and semantic errors in patients with mild AD, patients with amnestic mild cognitive impairment (aMCI), and normal controls by examining their spontaneous answers on the Boston Naming Test (BNT) and verifying whether they needed or were benefited by semantic and phonemic cues. The errors in spontaneous answers were classified in four mutually exclusive categories (semantic errors, visual paragnosia, phonological errors, and omission errors), and the semantic errors were further subclassified as coordinate, superordinate, and circumlocutory. Patients with aMCI performed normally on the BNT and needed fewer semantic and phonemic cues than patients with mild AD. After semantic cues, subjects with aMCI and control subjects gave more correct answers than patients with mild AD, but after phonemic cues, there was no difference between the three groups, suggesting that the low performance of patients with AD cannot be completely explained by semantic breakdown. Patterns of spontaneous naming errors and subtypes of semantic errors were similar in the three groups, with decreasing error frequency from coordinate to superordinate to circumlocutory subtypes.

The Role of Executive Function in the Semantic Comprehension Deficits of Stroke Aphasia and Semantic Dementia

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Curtiss Chapman

2015-05-01

Results from 5 SD patients and 4 SA patients in our ongoing study suggest similar patterns of impairment on both semantic and executive function tasks for both patient groups. Both showed multi-modal semantic deficits via poor performance on at least 3 out of 5 semantic tasks tapping different modalities. Also, SA and SD patients showed no difference in consistency across semantic tasks (see Fig. 1a & b. Both groups also showed consistently poor performance on trail-making and verbal Stroop tasks compared to controls (see Figs. 1c & 1d. SD patients seem to be less impaired on both span measures (word span range: 2.17 – 4.43; digit span: 3.17 – 5.5 than SA patients (word span range: 1.63 – 3.75; digit span: 1.17 – 4.17, and performance was variable for both groups on non-verbal Stroop and picture-word interference. SD patients found many executive tasks too difficult to understand, which may be the reason for limited prior data for them on EF tasks.. These findings suggest that the use of syndrome categories like semantic dementia and comprehension-impaired stroke aphasia are not useful in distinguishing between storage and access deficits. Patients classified as having SD seem as likely as SA patients to have certain kinds of executive deficits and SA patients may be as likely as SD patients to show consistency across semantic tasks. The results imply that some other behavioral or neuroanatomical basis rather than syndrome classification should be used to address the hypothesized separation of storage vs. control aspects of semantic memory.

Enabling Semantic Queries Against the Spatial Database

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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.

Similarity Measure of Graphs

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Amine Labriji

2017-07-01

Full Text Available The topic of identifying the similarity of graphs was considered as highly recommended research field in the Web semantic, artificial intelligence, the shape recognition and information research. One of the fundamental problems of graph databases is finding similar graphs to a graph query. Existing approaches dealing with this problem are usually based on the nodes and arcs of the two graphs, regardless of parental semantic links. For instance, a common connection is not identified as being part of the similarity of two graphs in cases like two graphs without common concepts, the measure of similarity based on the union of two graphs, or the one based on the notion of maximum common sub-graph (SCM, or the distance of edition of graphs. This leads to an inadequate situation in the context of information research. To overcome this problem, we suggest a new measure of similarity between graphs, based on the similarity measure of Wu and Palmer. We have shown that this new measure satisfies the properties of a measure of similarities and we applied this new measure on examples. The results show that our measure provides a run time with a gain of time compared to existing approaches. In addition, we compared the relevance of the similarity values obtained, it appears that this new graphs measure is advantageous and  offers a contribution to solving the problem mentioned above.

Are Judgments of Semantic Relatedness Systematically Impaired in Alzheimer's Disease?

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Hornberger, M.; Bell, B.; Graham, K. S.; Rogers, T. T.

2009-01-01

We employed a triadic comparison task in patients with Alzheimer's disease (AD) and healthy controls to contrast (a) multidimensional scaling (MDS) and accuracy-based assessments of semantic memory, and (b) degraded-store versus degraded-access accounts of semantic impairment in Alzheimer's disease (AD). Similar to other studies using triadic…

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

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Sui, Jie; Humphreys, Glyn W

2013-11-01

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

Propagating semantic information in biochemical network models

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Schulz Marvin

2012-01-01

Full Text Available Abstract Background To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation. Results A new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotations for non-annotated model elements. Conclusions Semantic propagation and model alignment are included in the open-source library semanticSBML, available on sourceforge. Online services for model alignment and for annotation prediction can be used at http://www.semanticsbml.org.

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.

Tableau Calculus for the Logic of Comparative Similarity over Arbitrary Distance Spaces

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Alenda, Régis; Olivetti, Nicola

The logic CSL (first introduced by Sheremet, Tishkovsky, Wolter and Zakharyaschev in 2005) allows one to reason about distance comparison and similarity comparison within a modal language. The logic can express assertions of the kind "A is closer/more similar to B than to C" and has a natural application to spatial reasoning, as well as to reasoning about concept similarity in ontologies. The semantics of CSL is defined in terms of models based on different classes of distance spaces and it generalizes the logic S4 u of topological spaces. In this paper we consider CSL defined over arbitrary distance spaces. The logic comprises a binary modality to represent comparative similarity and a unary modality to express the existence of the minimum of a set of distances. We first show that the semantics of CSL can be equivalently defined in terms of preferential models. As a consequence we obtain the finite model property of the logic with respect to its preferential semantic, a property that does not hold with respect to the original distance-space semantics. Next we present an analytic tableau calculus based on its preferential semantics. The calculus provides a decision procedure for the logic, its termination is obtained by imposing suitable blocking restrictions.

Semantic querying of data guided by Formal Concept Analysis

OpenAIRE

Codocedo , Victor; Lykourentzou , Ioanna; Napoli , Amedeo

2012-01-01

International audience; In this paper we present a novel approach to handle querying over a concept lattice of documents and annotations. We focus on the problem of "non-matching documents", which are those that, despite being semantically relevant to the user query, do not contain the query's elements and hence cannot be retrieved by typical string matching approaches. In order to find these documents, we modify the initial user query using the concept lattice as a guide. We achieve this by ...

Discovering Central Practitioners in a Medical Discussion Forum Using Semantic Web Analytics.

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Rajabi, Enayat; Abidi, Syed Sibte Raza

2017-01-01

The aim of this paper is to investigate semantic web based methods to enrich and transform a medical discussion forum in order to perform semantics-driven social network analysis. We use the centrality measures as well as semantic similarity metrics to identify the most influential practitioners within a discussion forum. The centrality results of our approach are in line with centrality measures produced by traditional SNA methods, thus validating the applicability of semantic web based methods for SNA, particularly for analyzing social networks for specialized discussion forums.

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,

Acoustic and semantic interference effects in words and pictures.

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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.

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

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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

Semantic relatedness and similarity of biomedical terms: examining the effects of recency, size, and section of biomedical publications on the performance of word2vec.

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Zhu, Yongjun; Yan, Erjia; Wang, Fei

2017-07-03

Understanding semantic relatedness and similarity between biomedical terms has a great impact on a variety of applications such as biomedical information retrieval, information extraction, and recommender systems. The objective of this study is to examine word2vec's ability in deriving semantic relatedness and similarity between biomedical terms from large publication data. Specifically, we focus on the effects of recency, size, and section of biomedical publication data on the performance of word2vec. We download abstracts of 18,777,129 articles from PubMed and 766,326 full-text articles from PubMed Central (PMC). The datasets are preprocessed and grouped into subsets by recency, size, and section. Word2vec models are trained on these subtests. Cosine similarities between biomedical terms obtained from the word2vec models are compared against reference standards. Performance of models trained on different subsets are compared to examine recency, size, and section effects. Models trained on recent datasets did not boost the performance. Models trained on larger datasets identified more pairs of biomedical terms than models trained on smaller datasets in relatedness task (from 368 at the 10% level to 494 at the 100% level) and similarity task (from 374 at the 10% level to 491 at the 100% level). The model trained on abstracts produced results that have higher correlations with the reference standards than the one trained on article bodies (i.e., 0.65 vs. 0.62 in the similarity task and 0.66 vs. 0.59 in the relatedness task). However, the latter identified more pairs of biomedical terms than the former (i.e., 344 vs. 498 in the similarity task and 339 vs. 503 in the relatedness task). Increasing the size of dataset does not always enhance the performance. Increasing the size of datasets can result in the identification of more relations of biomedical terms even though it does not guarantee better precision. As summaries of research articles, compared with article

Generative Semantics.

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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…

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

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Petter Kallioinen

2016-08-01

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

Cognitive Systematicity of Semantic Change: Cross-Linguistic Evidence

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Baseel A. AlBzour

2016-05-01

Full Text Available Banking on intrinsic generative assumptions of cognitive semantics, this paper is a humble attempt that specifically sheds light on some major aspects of overtly intricate yet covertly systematic interaction that steers our conceptual processing of inherent semantic and pragmatic changes. The basic premises of such cognitive operations stem from yet may exceed the limitations of Elizabeth Traugott’s and Eve Sweetser’s historical pragmatic approach that elaborately envisages such lexical changes as meaning relations with their metaphorically polysemous progress in light of relevant epistemic constraints that can help us decode ambiguous components of some functional and lexical categories. Therefore, this paper examines in principle how schematic lexical meaning can be cross-linguistically and cross-culturally traced, handled and perceived in order to cater for an optimal matrix and some rule-governed clues and rules that may explain the internal universal design and flow of semanticity and pragmaticity in charge of such linguistic behavior. The data this study exploits and explores draw on some English and Arabic representative examples that can satisfactorily exhibit an interesting well-established cognitive mechanism that can reveal the role of Homo sapiens’ encyclopedic and collective faculty vis-à-vis such word processing; the data primarily encompass the English words silly, simple, innocent and naïve as well as their Arabic counterparts.

[Electrophysiological bases of semantic processing of objects].

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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.

Exploring DBpedia and Wikipedia for Portuguese Semantic Relationship Extraction

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David Soares Batista

2013-07-01

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

Bio-jETI: a framework for semantics-based service composition

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Margaria Tiziana

2009-10-01

Full Text Available Abstract Background The development of bioinformatics databases, algorithms, and tools throughout the last years has lead to a highly distributed world of bioinformatics services. Without adequate management and development support, in silico researchers are hardly able to exploit the potential of building complex, specialized analysis processes from these services. The Semantic Web aims at thoroughly equipping individual data and services with machine-processable meta-information, while workflow systems support the construction of service compositions. However, even in this combination, in silico researchers currently would have to deal manually with the service interfaces, the adequacy of the semantic annotations, type incompatibilities, and the consistency of service compositions. Results In this paper, we demonstrate by means of two examples how Semantic Web technology together with an adequate domain modelling frees in silico researchers from dealing with interfaces, types, and inconsistencies. In Bio-jETI, bioinformatics services can be graphically combined to complex services without worrying about details of their interfaces or about type mismatches of the composition. These issues are taken care of at the semantic level by Bio-jETI's model checking and synthesis features. Whenever possible, they automatically resolve type mismatches in the considered service setting. Otherwise, they graphically indicate impossible/incorrect service combinations. In the latter case, the workflow developer may either modify his service composition using semantically similar services, or ask for help in developing the missing mediator that correctly bridges the detected type gap. Newly developed mediators should then be adequately annotated semantically, and added to the service library for later reuse in similar situations. Conclusion We show the power of semantic annotations in an adequately modelled and semantically enabled domain setting. Using model

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

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

2005-01-01

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

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

Losing sight of the future: Impaired semantic prospection following medial temporal lobe lesions

Science.gov (United States)

Race, Elizabeth; Keane, Margaret M.; Verfaellie, Mieke

2012-01-01

The ability to imagine the future (prospection) relies on many of the same brain regions that support memory for the past. To date, scientific research has primarily focused on the neural substrates of episodic forms of prospection (mental simulation of spatiotemporally specific future events) whereas little is known about the neural substrates of semantic prospection (mental simulation of future nonpersonal facts). Of particular interest is the role of the medial temporal lobes, and specifically the hippocampus. While the hippocampus has been proposed to play a key role in episodic prospection, recent evidence suggests that it may not play a similar role in semantic prospection. To examine this possibility, amnesic patients with medial temporal lobe (MTL) lesions were asked to imagine future issues occurring in the public domain. The results showed that patients could list general semantic facts about the future, but when probed to elaborate, patients produced impoverished descriptions that lacked semantic detail. This impairment occurred despite intact performance on standard neuropsychological tests of semantic processing, and did not simply reflect deficits in narrative construction. The performance of a patient with damage limited to the hippocampus was similar to that of the remaining MTL patients and amnesic patients’ impaired elaboration of the semantic future correlated with their impaired elaboration of the semantic past. Together, these results provide novel evidence from MTL amnesia that memory and prospection are linked in the semantic domain and reveal that the medial temporal lobes play a critical role in the construction of detailed, multi-element semantic simulations. PMID:23197413

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.

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

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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.

Ontology-based semantic information technology for safeguards: opportunities and challenges

International Nuclear Information System (INIS)

McDaniel, Michael

2014-01-01

The challenge of efficiently handling large volumes of heterogeneous information is a barrier to more effective safeguards implementation. With the emergence of new technologies for generating and collecting information this is an issue common to many industries and problem domains. Several diverse information‑intensive fields are developing and adopting ontology‑based semantic information technology solutions to address issues of information integration, federation and interoperability. Ontology, in this context, refers to the formal specification of the content, structure, and logic of knowledge within a domain of interest. Ontology‑based semantic information technologies have the potential to impact nearly every level of safeguards implementation, from information collection and integration, to personnel training and knowledge retention, to planning and analysis. However, substantial challenges remain before the full benefits of semantic technology can be realized. Perhaps the most significant challenge is the development of a nuclear fuel cycle ontology. For safeguards, existing knowledge resources such as the IAEA’s Physical Model and established upper level ontologies can be used as starting points for ontology development, but a concerted effort must be taken by the safeguards community for such an activity to be successful. This paper provides a brief background of ontologies and semantic information technology, demonstrates how these technologies are used in other areas, offers examples of how ontologies can be applied to safeguards, and discusses the challenges of developing and implementing this technology as well as a possible path forward.

Ways of making-sense: Local gamma synchronization reveals differences between semantic processing induced by music and language.

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Barraza, Paulo; Chavez, Mario; Rodríguez, Eugenio

2016-01-01

Similar to linguistic stimuli, music can also prime the meaning of a subsequent word. However, it is so far unknown what is the brain dynamics underlying the semantic priming effect induced by music, and its relation to language. To elucidate these issues, we compare the brain oscillatory response to visual words that have been semantically primed either by a musical excerpt or by an auditory sentence. We found that semantic violation between music-word pairs triggers a classical ERP N400, and induces a sustained increase of long-distance theta phase synchrony, along with a transient increase of local gamma activity. Similar results were observed after linguistic semantic violation except for gamma activity, which increased after semantic congruence between sentence-word pairs. Our findings indicate that local gamma activity is a neural marker that signals different ways of semantic processing between music and language, revealing the dynamic and self-organized nature of the semantic processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Concepts and tools for the design of semantical databases

CERN Document Server

Meersman, Robert A

1991-01-01

The design and implementation of modern more "semantical" databases involves the use of high-level conceptual abstraction mechanisms and methodologies. An illustration of this process is given using the NIAM method and notation (lecture 1), its transformation into relational database with triggers (e.g. using SYBASE0 (lecture 2) and a study of the requirements for suitable tools (RIDL*) and their extension and applicability for e.g. object-oriented databases. A case study defined by a complex database for document handling will be used as example (lecture 3).

Automatic markerless registration of point clouds with semantic-keypoint-based 4-points congruent sets

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Ge, Xuming

2017-08-01

The coarse registration of point clouds from urban building scenes has become a key topic in applications of terrestrial laser scanning technology. Sampling-based algorithms in the random sample consensus (RANSAC) model have emerged as mainstream solutions to address coarse registration problems. In this paper, we propose a novel combined solution to automatically align two markerless point clouds from building scenes. Firstly, the method segments non-ground points from ground points. Secondly, the proposed method detects feature points from each cross section and then obtains semantic keypoints by connecting feature points with specific rules. Finally, the detected semantic keypoints from two point clouds act as inputs to a modified 4PCS algorithm. Examples are presented and the results compared with those of K-4PCS to demonstrate the main contributions of the proposed method, which are the extension of the original 4PCS to handle heavy datasets and the use of semantic keypoints to improve K-4PCS in relation to registration accuracy and computational efficiency.

Interests diffusion on a semantic multiplex. Comparing Computer Science and American Physical Society communities

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D'Agostino, Gregorio; De Nicola, Antonio

2016-10-01

Exploiting the information about members of a Social Network (SN) represents one of the most attractive and dwelling subjects for both academic and applied scientists. The community of Complexity Science and especially those researchers working on multiplex social systems are devoting increasing efforts to outline general laws, models, and theories, to the purpose of predicting emergent phenomena in SN's (e.g. success of a product). On the other side the semantic web community aims at engineering a new generation of advanced services tailored to specific people needs. This implies defining constructs, models and methods for handling the semantic layer of SNs. We combined models and techniques from both the former fields to provide a hybrid approach to understand a basic (yet complex) phenomenon: the propagation of individual interests along the social networks. Since information may move along different social networks, one should take into account a multiplex structure. Therefore we introduced the notion of "Semantic Multiplex". In this paper we analyse two different semantic social networks represented by authors publishing in the Computer Science and those in the American Physical Society Journals. The comparison allows to outline common and specific features.

The Husserlian Lebenswelt and the Semantic Conception of Theories

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Raúl Milone

2007-12-01

Full Text Available This article establishes some important similarities between Husserl’sthoughts about the nature of science and the semantic view of scientific theories. This last conception affirms that empirical theories do not describe the world as it is, but that they idealize and represent it using structural models. In this sense and prima facie, the semantic conception coincides with Husserl’s point of view regarding the life-world and the world of science.

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.

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

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Alice F Jackson

2014-05-01

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

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

Science.gov (United States)

Jackson, Alice F; Bolger, Donald J

2014-01-01

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

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

OpenAIRE

Krause, Jürgen

2008-01-01

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

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

Science.gov (United States)

Ježek, Petr; Mouček, Roman

2015-01-01

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

Semantic and Phonological Loop Effects on Verbal Working Memory in Middle-Age Adults with Mental Retardation

Science.gov (United States)

Kittler, Phyllis; Krinsky-McHale, Sharon J.; Devenny, Darlynne A.

2004-01-01

Semantic and phonological loop effects on verbal working memory were examined among middle-age adults with Down syndrome and those with unspecified mental retardation in the context of Baddeley's working memory model. Recall was poorer for phonologically similar, semantically similar, and long words compared to recall of dissimilar short words.…

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

The neural basis for novel semantic categorization.

Science.gov (United States)

Koenig, Phyllis; Smith, Edward E; Glosser, Guila; DeVita, Chris; Moore, Peachie; McMillan, Corey; Gee, Jim; Grossman, Murray

2005-01-15

We monitored regional cerebral activity with BOLD fMRI during acquisition of a novel semantic category and subsequent categorization of test stimuli by a rule-based strategy or a similarity-based strategy. We observed different patterns of activation in direct comparisons of rule- and similarity-based categorization. During rule-based category acquisition, subjects recruited anterior cingulate, thalamic, and parietal regions to support selective attention to perceptual features, and left inferior frontal cortex to helps maintain rules in working memory. Subsequent rule-based categorization revealed anterior cingulate and parietal activation while judging stimuli whose conformity with the rules was readily apparent, and left inferior frontal recruitment during judgments of stimuli whose conformity was less apparent. By comparison, similarity-based category acquisition showed recruitment of anterior prefrontal and posterior cingulate regions, presumably to support successful retrieval of previously encountered exemplars from long-term memory, and bilateral temporal-parietal activation for perceptual feature integration. Subsequent similarity-based categorization revealed temporal-parietal, posterior cingulate, and anterior prefrontal activation. These findings suggest that large-scale networks support relatively distinct categorization processes during the acquisition and judgment of semantic category knowledge.

Knowledge, Skills and Competence Modelling in Nuclear Engineering Domain using Singular Value Decomposition (SVD) and Latent Semantic Analysis (LSA)

International Nuclear Information System (INIS)

Kuo, V.

2016-01-01

Full text: The European Qualifications Framework categorizes learning objectives into three qualifiers “knowledge”, “skills”, and “competences” (KSCs) to help improve the comparability between different fields and disciplines. However, the management of KSCs remains a great challenge given their semantic fuzziness. Similar texts may describe different concepts and different texts may describe similar concepts among different domains. This is difficult for the indexing, searching and matching of semantically similar KSCs within an information system, to facilitate transfer and mobility of KSCs. We present a working example using a semantic inference method known as Latent Semantic Analysis, employing a matrix operation called Singular Value Decomposition, which have been shown to infer semantic associations within unstructured textual data comparable to that of human interpretations. In our example, a few natural language text passages representing KSCs in the nuclear sector are used to demonstrate the capabilities of the system. It can be shown that LSA is able to infer latent semantic associations between texts, and cluster and match separate text passages semantically based on these associations. We propose this methodology for modelling existing natural language KSCs in the nuclear domain so they can be semantically queried, retrieved and filtered upon request. (author

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

A THREE-STEP SPATIAL-TEMPORAL-SEMANTIC CLUSTERING METHOD FOR HUMAN ACTIVITY PATTERN ANALYSIS

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W. Huang

2016-06-01

Full Text Available How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time to four dimensions (space, time and semantics. More specifically, not only a location and time that people stay and spend are collected, but also what people “say” for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The

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

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

2009-09-23

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

Phonological learning in semantic dementia.

Science.gov (United States)

Jefferies, Elizabeth; Bott, Samantha; Ehsan, Sheeba; Lambon Ralph, Matthew A

2011-04-01

Patients with semantic dementia (SD) have anterior temporal lobe (ATL) atrophy that gives rise to a highly selective deterioration of semantic knowledge. Despite pronounced anomia and poor comprehension of words and pictures, SD patients have well-formed, fluent speech and normal digit span. Given the intimate connection between phonological STM and word learning revealed by both neuropsychological and developmental studies, SD patients might be expected to show good acquisition of new phonological forms, even though their ability to map these onto meanings is impaired. In contradiction of these predictions, a limited amount of previous research has found poor learning of new phonological forms in SD. In a series of experiments, we examined whether SD patient, GE, could learn novel phonological sequences and, if so, under which circumstances. GE showed normal benefits of phonological knowledge in STM (i.e., normal phonotactic frequency and phonological similarity effects) but reduced support from semantic memory (i.e., poor immediate serial recall for semantically degraded words, characterised by frequent item errors). Next, we demonstrated normal learning of serial order information for repeated lists of single-digit number words using the Hebb paradigm: these items were well-understood allowing them to be repeated without frequent item errors. In contrast, patient GE showed little learning of nonsense syllable sequences using the same Hebb paradigm. Detailed analysis revealed that both GE and the controls showed a tendency to learn their own errors as opposed to the target items. Finally, we showed normal learning of phonological sequences for GE when he was prevented from repeating his errors. These findings confirm that the ATL atrophy in SD disrupts phonological processing for semantically degraded words but leaves the phonological architecture intact. Consequently, when item errors are minimised, phonological STM can support the acquisition of new phoneme

Compiling Dictionaries Using Semantic Domains*

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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

SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

Science.gov (United States)

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

2004-01-01

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

A service-oriented distributed semantic mediator: integrating multiscale biomedical information.

Science.gov (United States)

Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus

2012-11-01

Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

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 �

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

Science.gov (United States)

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

2014-01-01

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

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

Science.gov (United States)

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

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Sara Pillay

2014-04-01

Full Text Available The correlation between semantic deficits and exception word regularization errors ("surface dyslexia" in semantic dementia has been taken as strong evidence for involvement of semantic codes in exception word pronunciation. Rare cases with semantic deficits but no exception word reading deficit have been explained as due to individual differences in reading strategy, but this account is hotly debated. Semantic dementia is a diffuse process that always includes semantic impairment, making lesion localization difficult and independent assessment of semantic deficits and reading errors impossible. We addressed this problem using voxel-based lesion symptom mapping in 38 patients with left hemisphere stroke. Patients were all right-handed, native English speakers and at least 6 months from stroke onset. Patients performed an oral reading task that included 80 exception words (words with inconsistent orthographic-phonologic correspondence, e.g., pint, plaid, glove. Regularization errors were defined as plausible but incorrect pronunciations based on application of spelling-sound correspondence rules (e.g., 'plaid' pronounced as "played". Two additional tests examined explicit semantic knowledge and retrieval. The first measured semantic substitution errors during naming of 80 standard line drawings of objects. This error type is generally presumed to arise at the level of concept selection. The second test (semantic matching required patients to match a printed sample word (e.g., bus with one of two alternative choice words (e.g., car, taxi on the basis of greater similarity of meaning. Lesions were labeled on high-resolution T1 MRI volumes using a semi-automated segmentation method, followed by diffeomorphic registration to a template. VLSM used an ANCOVA approach to remove variance due to age, education, and total lesion volume. Regularization errors during reading were correlated with damage in the posterior half of the middle temporal gyrus and

Semantic guidance of eye movements in real-world scenes

OpenAIRE

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

2011-01-01

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 movemen...

Text Summarization Using FrameNet-Based Semantic Graph Model

Directory of Open Access Journals (Sweden)

Xu Han

2016-01-01

Full Text Available Text summarization is to generate a condensed version of the original document. The major issues for text summarization are eliminating redundant information, identifying important difference among documents, and recovering the informative content. This paper proposes a Semantic Graph Model which exploits the semantic information of sentence using FSGM. FSGM treats sentences as vertexes while the semantic relationship as the edges. It uses FrameNet and word embedding to calculate the similarity of sentences. This method assigns weight to both sentence nodes and edges. After all, it proposes an improved method to rank these sentences, considering both internal and external information. The experimental results show that the applicability of the model to summarize text is feasible and effective.

Alternating-Offers Protocol for Multi-issue Bilateral Negotiation in Semantic-Enabled Marketplaces

Science.gov (United States)

Ragone, Azzurra; di Noia, Tommaso; di Sciascio, Eugenio; Donini, Francesco M.

We present a semantic-based approach to multi-issue bilateral negotiation for e-commerce. We use Description Logics to model advertisements, and relations among issues as axioms in a TBox. We then introduce a logic-based alternating-offers protocol, able to handle conflicting information, that merges non-standard reasoning services in Description Logics with utility thoery to find the most suitable agreements. We illustrate and motivate the theoretical framework, the logical language, and the negotiation protocol.

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

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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.

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

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Marelli Marco

2017-01-01

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

Semantic interference in picture naming during dual-task performance does not vary with reading ability.

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Piai, Vitória; Roelofs, Ardi; Roete, Ingeborg

2015-01-01

Previous dual-task studies examining the locus of semantic interference of distractor words in picture naming have obtained diverging results. In these studies, participants manually responded to tones and named pictures while ignoring distractor words (picture-word interference, PWI) with varying stimulus onset asynchrony (SOA) between tone and PWI stimulus. Whereas some studies observed no semantic interference at short SOAs, other studies observed effects of similar magnitude at short and long SOAs. The absence of semantic interference in some studies may perhaps be due to better reading skill of participants in these than in the other studies. According to such a reading-ability account, participants' reading skill should be predictive of the magnitude of their interference effect at short SOAs. To test this account, we conducted a dual-task study with tone discrimination and PWI tasks and measured participants' reading ability. The semantic interference effect was of similar magnitude at both short and long SOAs. Participants' reading ability was predictive of their naming speed but not of their semantic interference effect, contrary to the reading ability account. We conclude that the magnitude of semantic interference in picture naming during dual-task performance does not depend on reading skill.

Neural correlates of concreteness in semantic categorization.

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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.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities.

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Liu, Ming; Xu, Yang; Hu, Haixiao; Mohammed, Abdul-Wahid

2016-12-21

With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities

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Ming Liu

2016-12-01

Full Text Available With the development of Machine-to-Machine (M2M technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C, Deployment (D, Resource (R and IOData (IO. Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities

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Liu, Ming; Xu, Yang; Hu, Haixiao; Mohammed, Abdul-Wahid

2016-01-01

With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design. PMID:28009818

Semantically Interoperable XML Data.

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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.

Semantically Interoperable XML Data

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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

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

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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

Semantic Role Labeling

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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

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

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

2007-01-01

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

UML 2 Semantics and Applications

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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

Phonological, visual, and semantic coding strategies and children's short-term picture memory span.

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Henry, Lucy A; Messer, David; Luger-Klein, Scarlett; Crane, Laura

2012-01-01

Three experiments addressed controversies in the previous literature on the development of phonological and other forms of short-term memory coding in children, using assessments of picture memory span that ruled out potentially confounding effects of verbal input and output. Picture materials were varied in terms of phonological similarity, visual similarity, semantic similarity, and word length. Older children (6/8-year-olds), but not younger children (4/5-year-olds), demonstrated robust and consistent phonological similarity and word length effects, indicating that they were using phonological coding strategies. This confirmed findings initially reported by Conrad (1971), but subsequently questioned by other authors. However, in contrast to some previous research, little evidence was found for a distinct visual coding stage at 4 years, casting doubt on assumptions that this is a developmental stage that consistently precedes phonological coding. There was some evidence for a dual visual and phonological coding stage prior to exclusive use of phonological coding at around 5-6 years. Evidence for semantic similarity effects was limited, suggesting that semantic coding is not a key method by which young children recall lists of pictures.

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

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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.

Semantic memory in object use.

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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.

Confusing similar words: ERP correlates of lexical-semantic processing in first language attrition and late second language acquisition.

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Kasparian, Kristina; Steinhauer, Karsten

2016-12-01

First language (L1) attrition is a socio-linguistic circumstance where second language (L2) learning coincides with changes in exposure and use of the native-L1. Attriters often report experiencing a decline in automaticity or proficiency in their L1 after a prolonged period in the L2 environment, while their L2 proficiency continues to strengthen. Investigating the neurocognitive correlates of attrition alongside those of late L2 acquisition addresses the question of whether the brain mechanisms underlying both L1 and L2 processing are strongly determined by proficiency, irrespective of whether the language was acquired from birth or in adulthood. Using event-related-potentials (ERPs), we examined lexical-semantic processing in Italian L1 attriters, compared to adult Italian L2 learners and to Italian monolingual native speakers. We contrasted the processing of classical lexical-semantic violations (Mismatch condition) with sentences that were equally semantically implausible but arguably trickier, as the target-noun was "swapped" with an orthographic neighbor that differed only in its final vowel and gender-marking morpheme (e.g., cappello (hat) vs. cappella (chapel)). Our aim was to determine whether sentences with such "confusable nouns" (Swap condition) would be processed as semantically correct by late L2 learners and L1 attriters, especially for those individuals with lower Italian proficiency scores. We found that lower-proficiency Italian speakers did not show significant N400 effects for Swap violations relative to correct sentences, regardless of whether Italian was the L1 or the L2. Crucially, N400 response profiles followed a continuum of "nativelikeness" predicted by Italian proficiency scores - high-proficiency attriters and high-proficiency Italian learners were indistinguishable from native controls, whereas attriters and L2 learners in the lower-proficiency range showed significantly reduced N400 effects for "Swap" errors. Importantly, attriters

An agent-based peer-to-peer architecture for semantic discovery of manufacturing services across virtual enterprises

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Zhang, Wenyu; Zhang, Shuai; Cai, Ming; Jian, Wu

2015-04-01

With the development of virtual enterprise (VE) paradigm, the usage of serviceoriented architecture (SOA) is increasingly being considered for facilitating the integration and utilisation of distributed manufacturing resources. However, due to the heterogeneous nature among VEs, the dynamic nature of a VE and the autonomous nature of each VE member, the lack of both sophisticated coordination mechanism in the popular centralised infrastructure and semantic expressivity in the existing SOA standards make the current centralised, syntactic service discovery method undesirable. This motivates the proposed agent-based peer-to-peer (P2P) architecture for semantic discovery of manufacturing services across VEs. Multi-agent technology provides autonomous and flexible problemsolving capabilities in dynamic and adaptive VE environments. Peer-to-peer overlay provides highly scalable coupling across decentralised VEs, each of which exhibiting as a peer composed of multiple agents dealing with manufacturing services. The proposed architecture utilises a novel, efficient, two-stage search strategy - semantic peer discovery and semantic service discovery - to handle the complex searches of manufacturing services across VEs through fast peer filtering. The operation and experimental evaluation of the prototype system are presented to validate the implementation of the proposed approach.

Evidence for the contribution of a threshold retrieval process to semantic memory.

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Kempnich, Maria; Urquhart, Josephine A; O'Connor, Akira R; Moulin, Chris J A

2017-10-01

It is widely held that episodic retrieval can recruit two processes: a threshold context retrieval process (recollection) and a continuous signal strength process (familiarity). Conversely the processes recruited during semantic retrieval are less well specified. We developed a semantic task analogous to single-item episodic recognition to interrogate semantic recognition receiver-operating characteristics (ROCs) for a marker of a threshold retrieval process. We fitted observed ROC points to three signal detection models: two models typically used in episodic recognition (unequal variance and dual-process signal detection models) and a novel dual-process recollect-to-reject (DP-RR) signal detection model that allows a threshold recollection process to aid both target identification and lure rejection. Given the nature of most semantic questions, we anticipated the DP-RR model would best fit the semantic task data. Experiment 1 (506 participants) provided evidence for a threshold retrieval process in semantic memory, with overall best fits to the DP-RR model. Experiment 2 (316 participants) found within-subjects estimates of episodic and semantic threshold retrieval to be uncorrelated. Our findings add weight to the proposal that semantic and episodic memory are served by similar dual-process retrieval systems, though the relationship between the two threshold processes needs to be more fully elucidated.

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

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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.

Hippocampal activation during retrieval of spatial context from episodic and semantic memory.

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Hoscheidt, Siobhan M; Nadel, Lynn; Payne, Jessica; Ryan, Lee

2010-10-15

The hippocampus, a region implicated in the processing of spatial information and episodic memory, is central to the debate concerning the relationship between episodic and semantic memory. Studies of medial temporal lobe amnesic patients provide evidence that the hippocampus is critical for the retrieval of episodic but not semantic memory. On the other hand, recent neuroimaging studies of intact individuals report hippocampal activation during retrieval of both autobiographical memories and semantic information that includes historical facts, famous faces, and categorical information, suggesting that episodic and semantic memory may engage the hippocampus during memory retrieval in similar ways. Few studies have matched episodic and semantic tasks for the degree to which they include spatial content, even though spatial content may be what drives hippocampal activation during semantic retrieval. To examine this issue, we conducted a functional magnetic resonance imaging (fMRI) study in which retrieval of spatial and nonspatial information was compared during an episodic and semantic recognition task. Results show that the hippocampus (1) participates preferentially in the retrieval of episodic memories; (2) is also engaged by retrieval of semantic memories, particularly those that include spatial information. These data suggest that sharp dissociations between episodic and semantic memory may be overly simplistic and that the hippocampus plays a role in the retrieval of spatial content whether drawn from a memory of one's own life experiences or real-world semantic knowledge. Published by Elsevier B.V.

Meinongian Semantics and Artificial Intelligence

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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.

Geospatial Semantics and the Semantic Web

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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

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

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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.

Impact of Semantic Relatedness on Associative Memory: An ERP Study

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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.

The role of orthography in the semantic activation of neighbors.

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Hino, Yasushi; Lupker, Stephen J; Taylor, Tamsen E

2012-09-01

There is now considerable evidence that a letter string can activate semantic information appropriate to its orthographic neighbors (e.g., Forster & Hector's, 2002, TURPLE effect). This phenomenon is the focus of the present research. Using Japanese words, we examined whether semantic activation of neighbors is driven directly by orthographic similarity alone or whether there is also a role for phonological similarity. In Experiment 1, using a relatedness judgment task in which a Kanji word-Katakana word pair was presented on each trial, an inhibitory effect was observed when the initial Kanji word was related to an orthographic and phonological neighbor of the Katakana word target but not when the initial Kanji word was related to a phonological but not orthographic neighbor of the Katakana word target. This result suggests that phonology plays little, if any, role in the activation of neighbors' semantics when reading familiar words. In Experiment 2, the targets were transcribed into Hiragana, a script they are typically not written in, requiring readers to engage in phonological coding. In that experiment, inhibitory effects were observed in both conditions. This result indicates that phonologically mediated semantic activation of neighbors will emerge when phonological processing is necessary in order to understand a written word (e.g., when that word is transcribed into an unfamiliar script). PsycINFO Database Record (c) 2012 APA, all rights reserved.

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

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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.

A Similarity-Ranking Method on Semantic Computing for Providing Information-Services in Station-Concierge System

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Motoki Yokoyama

2017-07-01

Full Text Available The prevalence of smartphones and wireless broadband networks have been progressing as a new Railway infomration environment.　According to the spread of such devices and information technology, various types of information can be obtained from databases connected to the Internet. One scenario of obtaining such a wide variety of information resources is in the phase of user’s transportation. This paper proposes an information provision system, named the Station Concierge System that matches the situation and intention of passengers. The purpose of this system is to estimate the needs of passengers like station staff or hotel concierge and to provide information resources that satisfy user’s expectations dynamically. The most important module of the system is constructed based on a new information ranking method for passenger intention prediction and service recommendation. This method has three main features, which are (1 projecting a user to semantic vector space by using her current context, (2 predicting the intention of a user based on selecting a semantic vector subspace, and (3 ranking the services by a descending order of relevant scores to the user’ intention. By comparing the predicted results of our method with those of two straightforward computation methods, the experimental studies show the effectiveness and efficiency of the proposed method. Using this system, users can obtain transit information and service map that dynamically matches their context.

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

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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.

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

Exploiting Speech for Automatic TV Delinearization: From Streams to Cross-Media Semantic Navigation

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Guinaudeau Camille

2011-01-01

Full Text Available The gradual migration of television from broadcast diffusion to Internet diffusion offers countless possibilities for the generation of rich navigable contents. However, it also raises numerous scientific issues regarding delinearization of TV streams and content enrichment. In this paper, we study how speech can be used at different levels of the delinearization process, using automatic speech transcription and natural language processing (NLP for the segmentation and characterization of TV programs and for the generation of semantic hyperlinks in videos. Transcript-based video delinearization requires natural language processing techniques robust to transcription peculiarities, such as transcription errors, and to domain and genre differences. We therefore propose to modify classical NLP techniques, initially designed for regular texts, to improve their robustness in the context of TV delinearization. We demonstrate that the modified NLP techniques can efficiently handle various types of TV material and be exploited for program description, for topic segmentation, and for the generation of semantic hyperlinks between multimedia contents. We illustrate the concept of cross-media semantic navigation with a description of our news navigation demonstrator presented during the NEM Summit 2009.

From Data to Semantic Information

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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.

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

Quantum aspects of semantic analysis and symbolic artificial intelligence

International Nuclear Information System (INIS)

Aerts, Diederik; Czachor, Marek

2004-01-01

Modern approaches to semantic analysis if reformulated as Hilbert-space problems reveal formal structures known from quantum mechanics. A similar situation is found in distributed representations of cognitive structures developed for the purpose of neural networks. We take a closer look at similarities and differences between the above two fields and quantum information theory. (letter to the editor)

Quantum aspects of semantic analysis and symbolic artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Aerts, Diederik [Centrum Leo Apostel (CLEA) and Foundations of the Exact Sciences (FUND), Vrije Universiteit Brussel, 1050 Brussels (Belgium); Czachor, Marek [Katedra Fizyki Teoretycznej i Metod Matematycznych, Politechnika Gdanska, 80-952 Gdansk (Poland)

2004-03-26

Modern approaches to semantic analysis if reformulated as Hilbert-space problems reveal formal structures known from quantum mechanics. A similar situation is found in distributed representations of cognitive structures developed for the purpose of neural networks. We take a closer look at similarities and differences between the above two fields and quantum information theory. (letter to the editor)

Practical solutions to implementing "Born Semantic" data systems

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Leadbetter, A.; Buck, J. J. H.; Stacey, P.

2015-12-01

The concept of data being "Born Semantic" has been proposed in recent years as a Semantic Web analogue to the idea of data being "born digital"[1], [2]. Within the "Born Semantic" concept, data are captured digitally and at a point close to the time of creation are annotated with markup terms from semantic web resources (controlled vocabularies, thesauri or ontologies). This allows heterogeneous data to be more easily ingested and amalgamated in near real-time due to the standards compliant annotation of the data. In taking the "Born Semantic" proposal from concept to operation, a number of difficulties have been encountered. For example, although there are recognised methods such as Header, Dictionary, Triples [3] for the compression, publication and dissemination of large volumes of triples these systems are not practical to deploy in the field on low-powered (both electrically and computationally) devices. Similarly, it is not practical for instruments to output fully formed semantically annotated data files if they are designed to be plugged into a modular system and the data to be centrally logged in the field as is the case on Argo floats and oceanographic gliders where internal bandwidth becomes an issue [2]. In light of these issues, this presentation will concentrate on pragmatic solutions being developed to the problem of generating Linked Data in near real-time systems. Specific examples from the European Commission SenseOCEAN project where Linked Data systems are being developed for autonomous underwater platforms, and from work being undertaken in the streaming of data from the Irish Galway Bay Cable Observatory initiative will be highlighted. Further, developments of a set of tools for the LogStash-ElasticSearch software ecosystem to allow the storing and retrieval of Linked Data will be introduced. References[1] A. Leadbetter & J. Fredericks, We have "born digital" - now what about "born semantic"?, European Geophysical Union General Assembly, 2014

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

Semantic richness and word learning in children with autism spectrum disorder.

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Gladfelter, Allison; Goffman, Lisa

2018-03-01

Semantically rich learning contexts facilitate semantic, phonological, and articulatory aspects of word learning in children with typical development (TD). However, because children with autism spectrum disorder (ASD) show differences at each of these processing levels, it is unclear whether they will benefit from semantic cues in the same manner as their typical peers. The goal of this study was to track how the inclusion of rich, sparse, or no semantic cues influences semantic, phonological, and articulatory aspects of word learning in children with ASD and TD over time. Twenty-four school-aged children (12 in each group), matched on expressive vocabulary, participated in an extended word learning paradigm. Performance on five measures of learning (referent identification, confrontation naming, defining, phonetic accuracy, and speech motor stability) were tracked across three sessions approximately one week apart to assess the influence of semantic richness on extended learning. Results indicate that children with ASD benefit from semantically rich learning contexts similarly to their peers with TD; however, one key difference between the two groups emerged - the children with ASD showed heightened shifts in speech motor stability. These findings offer insights into common learning mechanisms in children with ASD and TD, as well as pointing to a potentially distinct speech motor learning trajectory in children with ASD, providing a window into the emergence of stereotypic vocalizations in these children. © 2017 John Wiley & Sons Ltd.

XSemantic: An Extension of LCA Based XML Semantic Search

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Supasitthimethee, Umaporn; Shimizu, Toshiyuki; Yoshikawa, Masatoshi; Porkaew, Kriengkrai

One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge of XML structure or learning a new user interface. However, the keyword search is ambiguous. The users may use different terms to search for the same information. Furthermore, it is difficult for a system to decide which node is likely to be chosen as a return node and how much information should be included in the result. To address these challenges, we propose an XML semantic search based on keywords called XSemantic. On the one hand, we give three definitions to complete in terms of semantics. Firstly, the semantic term expansion, our system is robust from the ambiguous keywords by using the domain ontology. Secondly, to return semantic meaningful answers, we automatically infer the return information from the user queries and take advantage of the shortest path to return meaningful connections between keywords. Thirdly, we present the semantic ranking that reflects the degree of similarity as well as the semantic relationship so that the search results with the higher relevance are presented to the users first. On the other hand, in the LCA and the proximity search approaches, we investigated the problem of information included in the search results. Therefore, we introduce the notion of the Lowest Common Element Ancestor (LCEA) and define our simple rule without any requirement on the schema information such as the DTD or XML Schema. The first experiment indicated that XSemantic not only properly infers the return information but also generates compact meaningful results. Additionally, the benefits of our proposed semantics are demonstrated by the second experiment.

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

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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

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

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

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

Process-oriented semantic web search

CERN Document Server

Tran, DT

2011-01-01

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

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.

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

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.

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

Semantic networks for odors and colors in Alzheimer's disease.

Science.gov (United States)

Razani, Jill; Chan, Agnes; Nordin, Steven; Murphy, Claire

2010-05-01

Impairment in odor-naming ability and in verbal and visual semantic networks raised the hypothesis of a breakdown in the semantic network for odors in Alzheimer's disease (AD). The current study addressed this hypothesis. Twenty-four individuals, half patients with probable AD and half control participants, performed triadic-similarity judgments for odors and colors, separately, which, utilizing the multidimensional scaling (MDS) technique of individual difference scaling analysis (INDSCAL), generated two-dimensional configurations of similarity. The abilities to match odors and colors with written name labels were assessed to investigate disease-related differences in ability to identify and conceptualize the stimuli. In addition, responses on attribute-sorting tasks, requiring the odor and color perceptions to be categorized as one polarity of a certain dimension, were obtained to allow for objective interpretation of the MDS spatial maps. Whereas comparison subjects generated spatial maps based predominantly on relatively abstract characteristics, patients with AD classified odors on perceptual characteristics. The maps for patients with AD also showed disorganized groupings and loose associations between odors. Their normal configurations for colors imply that the patients were able to comprehend the task per se. The data for label matching and for attribute sorting provide further evidence for a disturbance in semantic odor memory in AD. The patients performed poorer than controls on both these odor tasks, implying that the ability to identify and/or conceptualize odors is impaired in AD. The results provide clear evidence for deterioration of the structure of semantic knowledge for odors in AD.

Semantic Memory Organization in Japanese Patients With Schizophrenia Examined With Category Fluency

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Chika Sumiyoshi

2018-03-01

Full Text Available BackgroundDisorganization of semantic memory in patients with schizophrenia has been studied by referring to their category fluency performance. Recently, data-mining techniques such as singular value decomposition (SVD analysis have been reported to be effective in elucidating the latent semantic memory structure in patients with schizophrenia. The aim of this study is to investigate semantic memory organization in patients with schizophrenia using a novel method based on data-mining approach.MethodCategory fluency data were collected from 181 patients with schizophrenia and 335 healthy controls at the Department of Psychiatry, Osaka University. The 20 most frequently reported animals were chosen for SVD analysis. In the two-dimensional (2D solution, item vectors (i.e., animal names were plotted in the 2D space of each group. In the six-dimensional (6D solution, inter-item similarities (i.e., cosines were calculated among items. Cosine charts were also created for the six most frequent items to show the similarities to other animal items.ResultsIn the 2D spatial representation, the six most frequent items were grouped in the same clusters (i.e., dog, cat as pet cluster, lion, tiger as wild/carnivorous cluster, and elephant, giraffe as wild/herbivorous cluster for patients and healthy adults. As for 6D spatial cosines, the correlations (Pearson’s r between 17 items commonly generated in the two groups were moderately high. However, cosine charts created for the three pairs from the six most frequent animals (dog–cat, lion–tiger, elephant–giraffe showed that pair-wise similarities between other animals were less salient in patients with schizophrenia.DiscussionSemantic memory organization in patients with schizophrenia, revealed by SVD analysis, did not appear to be seriously impaired in the 2D space representation, maintaining a clustering structure similar to that in healthy controls for common animals. However, the coherence of those

Structured Semantic Knowledge Can Emerge Automatically from Predicting Word Sequences in Child-Directed Speech

Science.gov (United States)

Huebner, Philip A.; Willits, Jon A.

2018-01-01

Previous research has suggested that distributional learning mechanisms may contribute to the acquisition of semantic knowledge. However, distributional learning mechanisms, statistical learning, and contemporary “deep learning” approaches have been criticized for being incapable of learning the kind of abstract and structured knowledge that many think is required for acquisition of semantic knowledge. In this paper, we show that recurrent neural networks, trained on noisy naturalistic speech to children, do in fact learn what appears to be abstract and structured knowledge. We trained two types of recurrent neural networks (Simple Recurrent Network, and Long Short-Term Memory) to predict word sequences in a 5-million-word corpus of speech directed to children ages 0–3 years old, and assessed what semantic knowledge they acquired. We found that learned internal representations are encoding various abstract grammatical and semantic features that are useful for predicting word sequences. Assessing the organization of semantic knowledge in terms of the similarity structure, we found evidence of emergent categorical and hierarchical structure in both models. We found that the Long Short-term Memory (LSTM) and SRN are both learning very similar kinds of representations, but the LSTM achieved higher levels of performance on a quantitative evaluation. We also trained a non-recurrent neural network, Skip-gram, on the same input to compare our results to the state-of-the-art in machine learning. We found that Skip-gram achieves relatively similar performance to the LSTM, but is representing words more in terms of thematic compared to taxonomic relations, and we provide reasons why this might be the case. Our findings show that a learning system that derives abstract, distributed representations for the purpose of predicting sequential dependencies in naturalistic language may provide insight into emergence of many properties of the developing semantic system. PMID

Structured Semantic Knowledge Can Emerge Automatically from Predicting Word Sequences in Child-Directed Speech

Directory of Open Access Journals (Sweden)

Philip A. Huebner

2018-02-01

Full Text Available Previous research has suggested that distributional learning mechanisms may contribute to the acquisition of semantic knowledge. However, distributional learning mechanisms, statistical learning, and contemporary “deep learning” approaches have been criticized for being incapable of learning the kind of abstract and structured knowledge that many think is required for acquisition of semantic knowledge. In this paper, we show that recurrent neural networks, trained on noisy naturalistic speech to children, do in fact learn what appears to be abstract and structured knowledge. We trained two types of recurrent neural networks (Simple Recurrent Network, and Long Short-Term Memory to predict word sequences in a 5-million-word corpus of speech directed to children ages 0–3 years old, and assessed what semantic knowledge they acquired. We found that learned internal representations are encoding various abstract grammatical and semantic features that are useful for predicting word sequences. Assessing the organization of semantic knowledge in terms of the similarity structure, we found evidence of emergent categorical and hierarchical structure in both models. We found that the Long Short-term Memory (LSTM and SRN are both learning very similar kinds of representations, but the LSTM achieved higher levels of performance on a quantitative evaluation. We also trained a non-recurrent neural network, Skip-gram, on the same input to compare our results to the state-of-the-art in machine learning. We found that Skip-gram achieves relatively similar performance to the LSTM, but is representing words more in terms of thematic compared to taxonomic relations, and we provide reasons why this might be the case. Our findings show that a learning system that derives abstract, distributed representations for the purpose of predicting sequential dependencies in naturalistic language may provide insight into emergence of many properties of the developing

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…

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.

A semantic web framework to integrate cancer omics data with biological knowledge.

Science.gov (United States)

Holford, Matthew E; McCusker, James P; Cheung, Kei-Hoi; Krauthammer, Michael

2012-01-25

The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.

Semantic mechanisms may be responsible for developing synesthesia

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Aleksandra eMroczko-Wąsowicz

2014-08-01

Full Text Available Currently, little is known about how synesthesia develops and which aspects of synesthesia can be acquired through a learning process. We review the increasing evidence for the role of semantic representations in the induction of synesthesia, and argue for the thesis that synesthetic abilities are developed and modified by semantic mechanisms. That is, in certain people semantic mechanisms associate concepts with perception-like experiences—and this association occurs in an extraordinary way. This phenomenon can be referred to as higher synesthesia or ideasthesia. The present analysis suggests that synesthesia develops during childhood and is being enriched further throughout the synesthetes’ lifetime; for example, the already existing concurrents may be adopted by novel inducers or new concurrents may be formed. For a deeper understanding of the origin and nature of synesthesia we propose to focus future research on two aspects: i the similarities between synesthesia and ordinary phenomenal experiences based on concepts, and ii the tight entanglement of perception, cognition and the conceptualization of the world. Most importantly, an explanation of how biological systems get to generate experiences, synesthetic or not, may have to involve an explanation of how we form semantic networks in general and what their role is in our ability to be aware of the surrounding world.

Executable specifications for hypothesis-based reasoning with Prolog and Constraint Handling Rules

DEFF Research Database (Denmark)

Christiansen, Henning

2009-01-01

Constraint Handling Rules (CHR) is an extension to Prolog which opens up a  spectrum of hypotheses-based reasoning in logic programs without additional interpretation overhead. Abduction with integrity constraints is one example of hypotheses-based reasoning which can be implemented directly...... in Prolog and CHR with a straightforward use of available and efficiently implemented facilities The present paper clarifies the semantic foundations for this way of doing abduction in CHR and Prolog as well as other examples  of hypotheses-based reasoning that is possible, including assumptive logic...

Subliminal semantic priming in speech.

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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.

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

DEFF Research Database (Denmark)

Nielsen, Finn Årup; Hansen, Lars Kai

2017-01-01

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

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

Semantic integration to identify overlapping functional modules in protein interaction networks

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Ramanathan Murali

2007-07-01

Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

Beyond the VWFA: The orthography-semantics interface in spelling and reading

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Purcell, Jeremy J.; Shea, Jennifer; Rapp, Brenda

2014-01-01

Lexical orthographic information provides the basis for recovering the meanings of words in reading and for generating correct word spellings in writing. Research has provided evidence that an area of the left ventral temporal cortex, a sub-region of what is often referred to as the Visual Word Form Area (VWFA), plays a significant role specifically in lexical orthographic processing. The current investigation goes beyond this previous work by examining the neurotopography of the interface of lexical orthography with semantics. We apply a novel lesion mapping approach with three individuals with acquired dysgraphia and dyslexia who suffered lesions to left ventral temporal cortex. To map cognitive processes to their neural substrates, this lesion mapping approach applies similar logical constraints as used in cognitive neuropsychological research. Using this approach, this investigation: (1) Identifies a region anterior to the VWFA that is important in the interface of orthographic information with semantics for reading and spelling; (2) Determines that, within this Orthography-Semantics Interface Region (OSIR), access to orthography from semantics (spelling) is topographically distinct from access to semantics from orthography (reading); (3) Provides evidence that, within this region, there is modality-specific access to and from lexical semantics for both spoken and written modalities, in both word production and comprehension. Overall, this study contributes to our understanding of the neural architecture at the lexical orthography-semantic-phonological interface within left ventral temporal cortex. PMID:24833190

Semantic Encoding Enhances the Pictorial Superiority Effect in the Oldest-Old

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Cherry, Katie E.; Brown, Jennifer Silva; Walker, Erin Jackson; Smitherman, Emily A.; Boudreaux, Emily O.; Volaufova, Julia; Jazwinski, S. Michal

2011-01-01

We examined the effect of a semantic orienting task during encoding on free recall and recognition of simple line drawings and matching words in middle-aged (44 to 59 years), older (60 to 89 years), and oldest-old (90 + years) adults. Participants studied line drawings and matching words presented in blocked order. Half of the participants were given a semantic orienting task and the other half received standard intentional learning instructions. Results confirmed that the pictorial superiority effect was greater in magnitude following semantic encoding compared to the control condition. Analyses of clustering in free recall revealed that oldest-old adults’ encoding and retrieval strategies were generally similar to the two younger groups. Self-reported strategy use was less frequent among the oldest-old adults. These data strongly suggest that semantic elaboration is an effective compensatory mechanism underlying preserved episodic memory performance that persists well into the ninth decade of life. PMID:22053814

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

identity; use of category cuing or similar techniques to discover the minimum semantic information needed to precipitate identification; some use of subjects trained in quantitative descriptive analysis to explore whether such training enhances semantic memory; and judicious use of mixtures to explore perceptual versus semantic errors of identification.

Algorithmic Procedure for Finding Semantically Related Journals.

Science.gov (United States)

Pudovkin, Alexander I.; Garfield, Eugene

2002-01-01

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

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

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

DEFF Research Database (Denmark)

Jensen, Kurt; Schmidt, Erik Meineche

1986-01-01

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

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

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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.…

Part-set cueing impairment & facilitation in semantic memory.

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Kelley, Matthew R; Parihar, Sushmeena A

2018-01-19

The present study explored the influence of part-set cues in semantic memory using tests of "free" recall, reconstruction of order, and serial recall. Nine distinct categories of information were used (e.g., Zodiac signs, Harry Potter books, Star Wars films, planets). The results showed part-set cueing impairment for all three "free" recall sets, whereas part-set cueing facilitation was evident for five of the six ordered sets. Generally, the present results parallel those often observed across episodic tasks, which could indicate that similar mechanisms contribute to part-set cueing effects in both episodic and semantic memory. A novel anchoring explanation of part-set cueing facilitation in order and spatial tasks is provided.

Further evidence that similar principles govern recall from episodic and semantic memory: the Canadian prime ministerial serial position function.

Science.gov (United States)

Neath, Ian; Saint-Aubin, Jean

2011-06-01

The serial position function, with its characteristic primacy and recency effects, is one of the most ubiquitous findings in episodic memory tasks. In contrast, there are only two demonstrations of such functions in tasks thought to tap semantic memory. Here, we provide a third demonstration, showing that free recall of the prime ministers of Canada also results in a serial position function. Scale Independent Memory, Perception, and Learning (SIMPLE), a local distinctiveness model of memory that was designed to account for serial position effects in episodic memory, fit the data. According to SIMPLE, serial position functions observed in episodic and semantic memory all reflect the relative distinctiveness principle: items will be well remembered to the extent that they are more distinct than competing items at the time of retrieval. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

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

Science.gov (United States)

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

2017-11-01

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

Semantic, phonologic, and verb fluency in Huntington's disease

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Mariana Jardim Azambuja

Full Text Available Abstract Verbal fluency tasks have been identified as important indicators of executive functioning impairment in patients with frontal lobe dysfunction. Although the usual evaluation of this ability considers phonologic and semantic criteria, there is some evidence that fluency of verbs would be more sensitive in disclosing frontostriatal physiopathology since frontal regions primarily mediate retrieval of verbs. Huntington's disease usually affects these circuitries. Objective: To compare three types of verbal fluency task in the assessment of frontal-striatal dysfunction in HD subjects. Methods: We studied 26 Huntington's disease subjects, divided into two subgroups: mild (11 and moderate (15 along with 26 normal volunteers matched for age, gender and schooling, for three types of verbal fluency: phonologic fluency (F-A-S, semantic fluency and fluency of verbs. Results: Huntington's disease subjects showed a significant reduction in the number of words correctly generated in the three tasks when compared to the normal group. Both controls and Huntington's disease subjects showed a similar pattern of decreasing task performance with the greatest number of words being generated by semantic elicitation followed by verbs and lastly phonologic criteria. We did not find greater production of verbs compared with F-A-S and semantic conditions. Moreover, the fluency of verbs distinguished only the moderate group from controls. Conclusion: Our results indicated that phonologic and semantic fluency can be used to evaluate executive functioning, proving more sensitive than verb fluency. However, it is important to point out that the diverse presentations of Huntington's disease means that an extended sample is necessary for more consistent analysis of this issue.

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

Semantics, contrastive linguistics and parallel corpora

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Violetta Koseska

2014-09-01

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

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

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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.

Distributed Database Semantic Integration of Wireless Sensor Network to Access the Environmental Monitoring System

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Ubaidillah Umar

2018-06-01

Full Text Available A wireless sensor network (WSN works continuously to gather information from sensors that generate large volumes of data to be handled and processed by applications. Current efforts in sensor networks focus more on networking and development services for a variety of applications and less on processing and integrating data from heterogeneous sensors. There is an increased need for information to become shareable across different sensors, database platforms, and applications that are not easily implemented in traditional database systems. To solve the issue of these large amounts of data from different servers and database platforms (including sensor data, a semantic sensor web service platform is needed to enable a machine to extract meaningful information from the sensor’s raw data. This additionally helps to minimize and simplify data processing and to deduce new information from existing data. This paper implements a semantic web data platform (SWDP to manage the distribution of data sensors based on the semantic database system. SWDP uses sensors for temperature, humidity, carbon monoxide, carbon dioxide, luminosity, and noise. The system uses the Sesame semantic web database for data processing and a WSN to distribute, minimize, and simplify information processing. The sensor nodes are distributed in different places to collect sensor data. The SWDP generates context information in the form of a resource description framework. The experiment results demonstrate that the SWDP is more efficient than the traditional database system in terms of memory usage and processing time.

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

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction.

Science.gov (United States)

Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A; Barak, Ohr; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2018-01-03

Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., , Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal 'hub' in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive-semantic goal representations, largely supported by executive regions such as frontal and parietal cortex, are thought to allow the generation of non-dominant aspects of knowledge when these are appropriate for the task or context. Semantic aphasia (SA) patients have executive-semantic deficits, and these are correlated with general executive impairment. If the CSC proposal is correct, patients with executive impairment should not only exhibit impaired semantic cognition, but should also show characteristics that align with those observed in SA. This possibility remains largely untested, as patients selected on the basis that they show executive impairment (i.e., with 'dysexecutive syndrome') have not been extensively tested on tasks tapping semantic control and have not been previously compared with SA cases. We explored conceptual processing in 12 patients showing symptoms consistent with dysexecutive syndrome (DYS) and 24 SA patients, using a range of multimodal semantic assessments which manipulated control demands. Patients with executive impairments, despite not being selected to show semantic impairments, nevertheless showed parallel patterns to SA cases. They showed strong effects of distractor strength, cues and miscues, and probe-target distance, plus minimal effects of word frequency on comprehension (unlike semantic dementia patients with degradation of conceptual knowledge). This supports a component process account of semantic cognition in which retrieval is shaped by control processes, and confirms that deficits in SA patients reflect

Putting semantics into the semantic web: how well can it capture biology?

Science.gov (United States)

Kazic, Toni

2006-01-01

Could the Semantic Web work for computations of biological interest in the way it's intended to work for movie reviews and commercial transactions? It would be wonderful if it could, so it's worth looking to see if its infrastructure is adequate to the job. The technologies of the Semantic Web make several crucial assumptions. I examine those assumptions; argue that they create significant problems; and suggest some alternative ways of achieving the Semantic Web's goals for biology.

The use of semantic similarity measures for optimally integrating heterogeneous Gene Ontology data from large scale annotation pipelines

Directory of Open Access Journals (Sweden)

Gaston K Mazandu

2014-08-01

Full Text Available With the advancement of new high throughput sequencing technologies, there has been an increase in the number of genome sequencing projects worldwide, which has yielded complete genome sequences of human, animals and plants. Subsequently, several labs have focused on genome annotation, consisting of assigning functions to gene products, mostly using Gene Ontology (GO terms. As a consequence, there is an increased heterogeneity in annotations across genomes due to different approaches used by different pipelines to infer these annotations and also due to the nature of the GO structure itself. This makes a curator's task difficult, even if they adhere to the established guidelines for assessing these protein annotations. Here we develop a genome-scale approach for integrating GO annotations from different pipelines using semantic similarity measures. We used this approach to identify inconsistencies and similarities in functional annotations between orthologs of human and Drosophila melanogaster, to assess the quality of GO annotations derived from InterPro2GO mappings compared to manually annotated GO annotations for the Drosophila melanogaster proteome from a FlyBase dataset and human, and to filter GO annotation data for these proteomes. Results obtained indicate that an efficient integration of GO annotations eliminates redundancy up to 27.08 and 22.32% in the Drosophila melanogaster and human GO annotation datasets, respectively. Furthermore, we identified lack of and missing annotations for some orthologs, and annotation mismatches between InterPro2GO and manual pipelines in these two proteomes, thus requiring further curation. This simplifies and facilitates tasks of curators in assessing protein annotations, reduces redundancy and eliminates inconsistencies in large annotation datasets for ease of comparative functional genomics.

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

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

DEFF Research Database (Denmark)

Danvy, Olivier

2008-01-01

We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fuse...... its transition function with its driver loop, obtaining the functional implementation of a big-step abstract machine; (2) we adjust this big-step abstract machine so that it is in defunctionalized form, obtaining the functional implementation of a second big-step abstract machine; (3) we...... refunctionalize this adjusted abstract machine, obtaining the functional implementation of a natural semantics in continuation style; and (4) we closure-unconvert this natural semantics, obtaining a compositional continuation-passing evaluation function which we identify as the functional implementation...

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.

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)....

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...

Safe handling of tritium

International Nuclear Information System (INIS)

1991-01-01

The main objective of this publication is to provide practical guidance and recommendations on operational radiation protection aspects related to the safe handling of tritium in laboratories, industrial-scale nuclear facilities such as heavy-water reactors, tritium removal plants and fission fuel reprocessing plants, and facilities for manufacturing commercial tritium-containing devices and radiochemicals. The requirements of nuclear fusion reactors are not addressed specifically, since there is as yet no tritium handling experience with them. However, much of the material covered is expected to be relevant to them as well. Annex III briefly addresses problems in the comparatively small-scale use of tritium at universities, medical research centres and similar establishments. However, the main subject of this publication is the handling of larger quantities of tritium. Operational aspects include designing for tritium safety, safe handling practice, the selection of tritium-compatible materials and equipment, exposure assessment, monitoring, contamination control and the design and use of personal protective equipment. This publication does not address the technologies involved in tritium control and cleanup of effluents, tritium removal, or immobilization and disposal of tritium wastes, nor does it address the environmental behaviour of tritium. Refs, figs and tabs

Semantic word category processing in semantic dementia and posterior cortical atrophy.

Science.gov (United States)

Shebani, Zubaida; Patterson, Karalyn; Nestor, Peter J; Diaz-de-Grenu, Lara Z; Dawson, Kate; Pulvermüller, Friedemann

2017-08-01

There is general agreement that perisylvian language cortex plays a major role in lexical and semantic processing; but the contribution of additional, more widespread, brain areas in the processing of different semantic word categories remains controversial. We investigated word processing in two groups of patients whose neurodegenerative diseases preferentially affect specific parts of the brain, to determine whether their performance would vary as a function of semantic categories proposed to recruit those brain regions. Cohorts with (i) Semantic Dementia (SD), who have anterior temporal-lobe atrophy, and (ii) Posterior Cortical Atrophy (PCA), who have predominantly parieto-occipital atrophy, performed a lexical decision test on words from five different lexico-semantic categories: colour (e.g., yellow), form (oval), number (seven), spatial prepositions (under) and function words (also). Sets of pseudo-word foils matched the target words in length and bi-/tri-gram frequency. Word-frequency was matched between the two visual word categories (colour and form) and across the three other categories (number, prepositions, and function words). Age-matched healthy individuals served as controls. Although broad word processing deficits were apparent in both patient groups, the deficit was strongest for colour words in SD and for spatial prepositions in PCA. The patterns of performance on the lexical decision task demonstrate (a) general lexicosemantic processing deficits in both groups, though more prominent in SD than in PCA, and (b) differential involvement of anterior-temporal and posterior-parietal cortex in the processing of specific semantic categories of words. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Semantics of data and service registration to advance interdisciplinary information and data access.

Science.gov (United States)

Fox, P. P.; McGuinness, D. L.; Raskin, R.; Sinha, A. K.

2008-12-01

In developing an application of semantic web methods and technologies to address the integration of heterogeneous and interdisciplinary earth-science datasets, we have developed methodologies for creating rich semantic descriptions (ontologies) of the application domains. We have leveraged and extended where possible existing ontology frameworks such as SWEET. As a result of this semantic approach, we have also utilized ontologic descriptions of key enabling elements of the application, such as the registration of datasets with ontologies at several levels of granularity. This has enabled the location and usage of the data across disciplines. We are also realizing the need to develop similar semantic registration of web service data holdings as well as those provided with community and/or standard markup languages (e.g. GeoSciML). This level of semantic enablement extending beyond domain terms and relations significantly enhances our ability to provide a coherent semantic data framework for data and information systems. Much of this work is on the frontier of technology development and we will present the current and near-future capabilities we are developing. This work arises from the Semantically-Enabled Science Data Integration (SESDI) project, which is an NASA/ESTO/ACCESS-funded project involving the High Altitude Observatory at the National Center for Atmospheric Research (NCAR), McGuinness Associates Consulting, NASA/JPL and Virginia Polytechnic University.

SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

Science.gov (United States)

Patton, Evan W.; Seyed, Patrice; Wang, Ping; Fu, Linyun; Dein, F. Joshua; Bristol, R. Sky; McGuinness, Deborah L.

2014-01-01

We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

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

Wernicke's Aphasia Reflects a Combination of Acoustic-Phonological and Semantic Control Deficits: A Case-Series Comparison of Wernicke's Aphasia, Semantic Dementia and Semantic Aphasia

Science.gov (United States)

Robson, Holly; Sage, Karen; Lambon Ralph, Matthew A.

2012-01-01

Wernicke's aphasia (WA) is the classical neurological model of comprehension impairment and, as a result, the posterior temporal lobe is assumed to be critical to semantic cognition. This conclusion is potentially confused by (a) the existence of patient groups with semantic impairment following damage to other brain regions (semantic dementia and…

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

Hierarchical Semantic Model of Geovideo

Directory of Open Access Journals (Sweden)

XIE Xiao

2015-05-01

Full Text Available The public security incidents were getting increasingly challenging with regard to their new features, including multi-scale mobility, multistage dynamic evolution, as well as spatiotemporal concurrency and uncertainty in the complex urban environment. However, the existing video models, which were used/designed for independent archive or local analysis of surveillance video, have seriously inhibited emergency response to the urgent requirements.Aiming at the explicit representation of change mechanism in video, the paper proposed a novel hierarchical geovideo semantic model using UML. This model was characterized by the hierarchical representation of both data structure and semantics based on the change-oriented three domains (feature domain, process domain and event domain instead of overall semantic description of video streaming; combining both geographical semantics and video content semantics, in support of global semantic association between multiple geovideo data. The public security incidents by video surveillance are inspected as an example to illustrate the validity of this model.

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…

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

Autonomic Semantic-Based Context-Aware Platform for Mobile Applications in Pervasive Environments

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Adel Alti

2016-09-01

Full Text Available Currently, the field of smart-* (home, city, health, tourism, etc. is naturally heterogeneous and multimedia oriented. In such a domain, there is an increasing usage of heterogeneous mobile devices, as well as captors transmitting data (IoT. They are highly connected and can be used for many different services, such as to monitor, to analyze and to display information to users. In this context, data management and adaptation in real time are becoming a challenging task. More precisely, at one time, it is necessary to handle in a dynamic, intelligent and transparent framework various data provided by multiple devices with several modalities. This paper presents a Kali-Smart platform, which is an autonomic semantic-based context-aware platform. It is based on semantic web technologies and a middleware providing autonomy and reasoning facilities. Moreover, Kali-Smart is generic and, as a consequence, offers to users a flexible infrastructure where they can easily control various interaction modalities of their own situations. An experimental study has been made to evaluate the performance and feasibility of the proposed platform.

The association of personal semantic memory to identity representations: insight into higher-order networks of autobiographical contents.

Science.gov (United States)

Grilli, Matthew D

2017-11-01

Identity representations are higher-order knowledge structures that organise autobiographical memories on the basis of personality and role-based themes of one's self-concept. In two experiments, the extent to which different types of personal semantic content are reflected in these higher-order networks of memories was investigated. Healthy, young adult participants generated identity representations that varied in remoteness of formation and verbally reflected on these themes in an open-ended narrative task. The narrative responses were scored for retrieval of episodic, experience-near personal semantic and experience-far (i.e., abstract) personal semantic contents. Results revealed that to reflect on remotely formed identity representations, experience-far personal semantic contents were retrieved more than experience-near personal semantic contents. In contrast, to reflect on recently formed identity representations, experience-near personal semantic contents were retrieved more than experience-far personal semantic contents. Although episodic memory contents were retrieved less than both personal semantic content types to reflect on remotely formed identity representations, this content type was retrieved at a similar frequency as experience-far personal semantic content to reflect on recently formed identity representations. These findings indicate that the association of personal semantic content to identity representations is robust and related to time since acquisition of these knowledge structures.

Semantic Representatives of the Concept

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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.

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.

Fast Semantic Segmentation of 3d Point Clouds with Strongly Varying Density

Science.gov (United States)

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

2016-06-01

We describe an effective and efficient method for point-wise semantic classification of 3D point clouds. The method can handle unstructured and inhomogeneous point clouds such as those derived from static terrestrial LiDAR or photogammetric reconstruction; and it is computationally efficient, making it possible to process point clouds with many millions of points in a matter of minutes. The key issue, both to cope with strong variations in point density and to bring down computation time, turns out to be careful handling of neighborhood relations. By choosing appropriate definitions of a point's (multi-scale) neighborhood, we obtain a feature set that is both expressive and fast to compute. We evaluate our classification method both on benchmark data from a mobile mapping platform and on a variety of large, terrestrial laser scans with greatly varying point density. The proposed feature set outperforms the state of the art with respect to per-point classification accuracy, while at the same time being much faster to compute.

Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services

Science.gov (United States)

Daniel, Christel; Ouagne, David; Sadou, Eric; Forsberg, Kerstin; Gilchrist, Mark Mc; Zapletal, Eric; Paris, Nicolas; Hussain, Sajjad; Jaulent, Marie-Christine; MD, Dipka Kalra

2016-01-01

With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data. PMID:27570649

Actively learning human gaze shifting paths for semantics-aware photo cropping.

Science.gov (United States)

Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

2014-05-01

Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.

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...

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…

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

Overlap in the functional neural systems involved in semantic and episodic memory retrieval.

Science.gov (United States)

Rajah, M N; McIntosh, A R

2005-03-01

Neuroimaging and neuropsychological data suggest that episodic and semantic memory may be mediated by distinct neural systems. However, an alternative perspective is that episodic and semantic memory represent different modes of processing within a single declarative memory system. To examine whether the multiple or the unitary system view better represents the data we conducted a network analysis using multivariate partial least squares (PLS ) activation analysis followed by covariance structural equation modeling (SEM) of positron emission tomography data obtained while healthy adults performed episodic and semantic verbal retrieval tasks. It is argued that if performance of episodic and semantic retrieval tasks are mediated by different memory systems, then there should differences in both regional activations and interregional correlations related to each type of retrieval task, respectively. The PLS results identified brain regions that were differentially active during episodic retrieval versus semantic retrieval. Regions that showed maximal differences in regional activity between episodic retrieval tasks were used to construct separate functional models for episodic and semantic retrieval. Omnibus tests of these functional models failed to find a significant difference across tasks for both functional models. The pattern of path coefficients for the episodic retrieval model were not different across tasks, nor were the path coefficients for the semantic retrieval model. The SEM results suggest that the same memory network/system was engaged across tasks, given the similarities in path coefficients. Therefore, activation differences between episodic and semantic retrieval may ref lect variation along a continuum of processing during task performance within the context of a single memory system.

X-Informatics: Practical Semantic Science

Science.gov (United States)

Borne, K. D.

2009-12-01

The discipline of data science is merging with multiple science disciplines to form new X-informatics research disciplines. They are almost too numerous to name, but they include geoinformatics, bioinformatics, cheminformatics, biodiversity informatics, ecoinformatics, materials informatics, and the emerging discipline of astroinformatics. Within any X-informatics discipline, the information granules are unique to that discipline -- e.g., gene sequences in bio, the sky object in astro, and the spatial object in geo (such as points, lines, and polygons in the vector model, and pixels in the raster model). Nevertheless the goals are similar: transparent data re-use across subdisciplines and within education settings, information and data integration and fusion, personalization of user interactions with the data collection, semantic search and retrieval, and knowledge discovery. The implementation of an X-informatics framework enables these semantic e-science research goals. We describe the concepts, challenges, and new developments associated with the new discipline of astroinformatics, and how geoinformatics provides valuable lessons learned and a model for practical semantic science within a traditional science discipline through the accretion of data science methodologies (such as formal metadata creation, data models, data mining, information retrieval, knowledge engineering, provenance, taxonomies, and ontologies). The emerging concept of data-as-a-service (DaaS) builds upon the concept of smart data (or data DNA) for intelligent data management, automated workflows, and intelligent processing. Smart data, defined through X-informatics, enables several practical semantic science use cases, including self-discovery, data intelligence, automatic recommendations, relevance analysis, dimension reduction, feature selection, constraint-based mining, interdisciplinary data re-use, knowledge-sharing, data use in education, and more. We describe these concepts within the

On the universal structure of human lexical semantics.

Science.gov (United States)

Youn, Hyejin; Sutton, Logan; Smith, Eric; Moore, Cristopher; Wilkins, Jon F; Maddieson, Ian; Croft, William; Bhattacharya, Tanmoy

2016-02-16

How universal is human conceptual structure? The way concepts are organized in the human brain may reflect distinct features of cultural, historical, and environmental background in addition to properties universal to human cognition. Semantics, or meaning expressed through language, provides indirect access to the underlying conceptual structure, but meaning is notoriously difficult to measure, let alone parameterize. Here, we provide an empirical measure of semantic proximity between concepts using cross-linguistic dictionaries to translate words to and from languages carefully selected to be representative of worldwide diversity. These translations reveal cases where a particular language uses a single "polysemous" word to express multiple concepts that another language represents using distinct words. We use the frequency of such polysemies linking two concepts as a measure of their semantic proximity and represent the pattern of these linkages by a weighted network. This network is highly structured: Certain concepts are far more prone to polysemy than others, and naturally interpretable clusters of closely related concepts emerge. Statistical analysis of the polysemies observed in a subset of the basic vocabulary shows that these structural properties are consistent across different language groups, and largely independent of geography, environment, and the presence or absence of a literary tradition. The methods developed here can be applied to any semantic domain to reveal the extent to which its conceptual structure is, similarly, a universal attribute of human cognition and language use.

Stimulus-independent semantic bias misdirects word recognition in older adults.

Science.gov (United States)

Rogers, Chad S; Wingfield, Arthur

2015-07-01

Older adults' normally adaptive use of semantic context to aid in word recognition can have a negative consequence of causing misrecognitions, especially when the word actually spoken sounds similar to a word that more closely fits the context. Word-pairs were presented to young and older adults, with the second word of the pair masked by multi-talker babble varying in signal-to-noise ratio. Results confirmed older adults' greater tendency to misidentify words based on their semantic context compared to the young adults, and to do so with a higher level of confidence. This age difference was unaffected by differences in the relative level of acoustic masking.

Differential cognitive processing of Kanji and Kana words: do orthographic and semantic codes function in parallel in word matching task.

Science.gov (United States)

Kawakami, A; Hatta, T; Kogure, T

2001-12-01

Relative engagements of the orthographic and semantic codes in Kanji and Hiragana word recognition were investigated. In Exp. 1, subjects judged whether the pairs of Kanji words (prime and target) presented sequentially were physically identical to each other in the word condition. In the sentence condition, subjects decided whether the target word was valid for the prime sentence presented in advance. The results showed that the response times to the target swords orthographically similar (to the prime) were significantly slower than to semantically related target words in the word condition and that this was also the case in the sentence condition. In Exp. 2, subjects judged whether the target word written in Hiragana was physically identical to the prime word in the word condition. In the sentence condition, subjects decided if the target word was valid for the previously presented prime sentence. Analysis indicated that response times to orthographically similar words were slower than to semantically related words in the word condition but not in the sentence condition wherein the response times to the semantically and orthographically similar words were largely the same. Based on these results, differential contributions of orthographic and semantic codes in cognitive processing of Japanese Kanji and Hiragana words was discussed.

Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.

Science.gov (United States)

Endert, A; Fiaux, P; North, C

2012-12-01

Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.

LAIR: A Language for Automated Semantics-Aware Text Sanitization based on Frame Semantics

DEFF Research Database (Denmark)

Hedegaard, Steffen; Houen, Søren; Simonsen, Jakob Grue

2009-01-01

We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires on...... with automated redaction of web pages for subjectively undesirable content; initial experiments suggest that using a small language based on semantic recognition of undesirable terms can be highly useful as a supplement to traditional methods of text sanitization.......We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires only...... limited prior programming experience. It neither contain scripting or I/O primitives, nor does it contain general loop constructions and is not Turing-complete. We have implemented a \\lair{} compiler and integrated it in a pipeline for automated redaction of web pages. We detail our experience...

Argument structure and the representation of abstract semantics.

Directory of Open Access Journals (Sweden)

Javier Rodríguez-Ferreiro

Full Text Available According to the dual coding theory, differences in the ease of retrieval between concrete and abstract words are related to the exclusive dependence of abstract semantics on linguistic information. Argument structure can be considered a measure of the complexity of the linguistic contexts that accompany a verb. If the retrieval of abstract verbs relies more on the linguistic codes they are associated to, we could expect a larger effect of argument structure for the processing of abstract verbs. In this study, sets of length- and frequency-matched verbs including 40 intransitive verbs, 40 transitive verbs taking simple complements, and 40 transitive verbs taking sentential complements were presented in separate lexical and grammatical decision tasks. Half of the verbs were concrete and half were abstract. Similar results were obtained in the two tasks, with significant effects of imageability and transitivity. However, the interaction between these two variables was not significant. These results conflict with hypotheses assuming a stronger reliance of abstract semantics on linguistic codes. In contrast, our data are in line with theories that link the ease of retrieval with availability and robustness of semantic information.

Argument structure and the representation of abstract semantics.

Science.gov (United States)

Rodríguez-Ferreiro, Javier; Andreu, Llorenç; Sanz-Torrent, Mònica

2014-01-01

According to the dual coding theory, differences in the ease of retrieval between concrete and abstract words are related to the exclusive dependence of abstract semantics on linguistic information. Argument structure can be considered a measure of the complexity of the linguistic contexts that accompany a verb. If the retrieval of abstract verbs relies more on the linguistic codes they are associated to, we could expect a larger effect of argument structure for the processing of abstract verbs. In this study, sets of length- and frequency-matched verbs including 40 intransitive verbs, 40 transitive verbs taking simple complements, and 40 transitive verbs taking sentential complements were presented in separate lexical and grammatical decision tasks. Half of the verbs were concrete and half were abstract. Similar results were obtained in the two tasks, with significant effects of imageability and transitivity. However, the interaction between these two variables was not significant. These results conflict with hypotheses assuming a stronger reliance of abstract semantics on linguistic codes. In contrast, our data are in line with theories that link the ease of retrieval with availability and robustness of semantic information.

Semantic dementia without surface dyslexia in Spanish: unimpaired reading with impaired semantics.

Science.gov (United States)

Wilson, Maximiliano A; Martínez-Cuitiño, Macarena

2012-01-01

Surface dyslexia has been attributed to an overreliance on the sub-lexical route for reading. Typically, surface dyslexic patients commit regularisation errors when reading irregular words. Also, semantic dementia has often been associated with surface dyslexia, leading to some explanations of the reading impairment that stress the role of semantics in irregular word reading. Nevertheless, some patients have been reported with unimpaired ability to read irregular words, even though they show severe comprehension impairment. We present the case of M.B., the first Spanish-speaking semantic dementia patient to be reported who shows unimpaired reading of non-words, regular words, and - most strikingly - irregular loan words. M.B. has severely impaired comprehension of the same words he reads correctly (whether regular or irregular). We argue that M.B.'s pattern of performance shows that irregular words can be correctly read even with impaired semantic knowledge corresponding to those words.

Perbandingan Hasil Deteksi Plagiarisme Dokumen dengan Metode Jaro-Winkler Distance dan Metode Latent Semantic Analysis

Directory of Open Access Journals (Sweden)

Tinaliah Tinaliah

2018-01-01

Full Text Available Various methods are applied in the application of plagiarism detection to help check the similarity of a document. Jaro-Winkler Distance can measure the distance between two strings. However, this method basically depends on the position of the word. Latent Semantic Analysis emphasizes the words contained in the document regardless of its linguistic character. This study compares the results of plagiarism detection using the Jaro-Winkler Distance and the Latent Semantic Analysis method. From comparing results of  Jaro-Winkler Distance method and Latent Semantic Analysis method, Jaro-Winkler Distance method is better than Latent Semantic Analysis method if using the same test data. Jaro-Winkler Distance method will give plagiarism result 100% and Latent Semantic Analysis method will give plagiarism result 97,14%. Beragam metode diterapkan dalam aplikasi deteksi plagiarisme untuk membantu mengecek tingkat kesamaan sebuah dokumen. Metode Jaro-Winkler Distance dapat mengukur kesamaan antara dua buah string dan sangat bergantung pada urutan atau posisi kata. Latent Semantic Analysis mementingkan kata-kata yang terkandung di dalam dokumen tanpa memperhatikan karakter linguistiknya. Penelitian ini melakukan perbandingan hasil deteksi plagiarisme dengan menggunakan metode Jaro-Winkler Distance dan metode Latent Semantic Analysis. Hasil pendeteksian plagiarisme dokumen menggunakan metode Jaro-Winkler Distance memberikan hasil yang lebih baik daripada metode Latent Semantic Analysis, yaitu jika data yang dibandingkan sama persis maka akan menghasilkan nilai plagiat sebesar 100%, sedangkan metode Latent Semantic Analysis menghasilkan nilai plagiat sebesar 97,14%.

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....

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

Science.gov (United States)

Keller, Richard M.; Ranjan, Shubha; Wei, Mie; Eshow, Michelle

2016-01-01

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

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

Semantics-based Automated Web Testing

Directory of Open Access Journals (Sweden)

Hai-Feng Guo

2015-08-01

Full Text Available We present TAO, a software testing tool performing automated test and oracle generation based on a semantic approach. TAO entangles grammar-based test generation with automated semantics evaluation using a denotational semantics framework. We show how TAO can be incorporated with the Selenium automation tool for automated web testing, and how TAO can be further extended to support automated delta debugging, where a failing web test script can be systematically reduced based on grammar-directed strategies. A real-life parking website is adopted throughout the paper to demonstrate the effectivity of our semantics-based web testing approach.

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:

Semantic Web and Contextual Information: Semantic Network Analysis of Online Journalistic Texts

Science.gov (United States)

Lim, Yon Soo

This study examines why contextual information is important to actualize the idea of semantic web, based on a case study of a socio-political issue in South Korea. For this study, semantic network analyses were conducted regarding English-language based 62 blog posts and 101 news stories on the web. The results indicated the differences of the meaning structures between blog posts and professional journalism as well as between conservative journalism and progressive journalism. From the results, this study ascertains empirical validity of current concerns about the practical application of the new web technology, and discusses how the semantic web should be developed.

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.

Denotational semantics in Synthetic Guarded Domain Theory

DEFF Research Database (Denmark)

Paviotti, Marco

In functional programming, features such as recursion, recursive types and general references are central. To define semantics of this kind of languages one needs to come up with certain definitions which may be non-trivial to show well-defined. This is because they are circular. Domain theory has...... been used to solve this kind of problems for specific languages, unfortunately, this technique does not scale for more featureful languages, which prevented it from being widely used. Step-indexing is a more general technique that has been used to break circularity of definitions. The idea is to tweak...... the definition by adding a well- founded structure that gives a handle for recursion. Guarded dependent Type Theory (gDTT) is a type theory which implements step-indexing via a unary modality used to guard recursive definitions. Every circular definition is well-defined as long as the recursive variable...

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’.

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...

Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

DEFF Research Database (Denmark)

Danvy, Olivier

2009-01-01

We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fus...

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.

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.

A Denotational Semantics for Logic Programming

DEFF Research Database (Denmark)

Frandsen, Gudmund Skovbjerg

A fully abstract denotational semantics for logic programming has not been constructed yet. In this paper we present a denotational semantics that is almost fully abstract. We take the meaning of a logic program to be an element in a Plotkin power domain of substitutions. In this way our result...... shows that standard domain constructions suffice, when giving a semantics for logic programming. Using the well-known fixpoint semantics of logic programming we have to consider two different fixpoints in order to obtain information about both successful and failed computations. In contrast, our...... semantics is uniform in that the (single) meaning of a logic program contains information about both successful, failed and infinite computations. Finally, based on the full abstractness result, we argue that the detail level of substitutions is needed in any denotational semantics for logic programming....

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.

CASL The Common Algebraic Specification Language Semantics

DEFF Research Database (Denmark)

Haxthausen, Anne

1998-01-01

This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the first complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop at Cachan in November 1998.......This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the first complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop at Cachan in November 1998....

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...

An fMRI study of semantic processing in men with schizophrenia

Science.gov (United States)

Kubicki, M.; McCarley, R.W.; Nestor, P.G.; Huh, T.; Kikinis, R.; Shenton, M.E.; Wible, C.G.

2009-01-01

As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus

An fMRI study of semantic processing in men with schizophrenia.

Science.gov (United States)

Kubicki, M; McCarley, R W; Nestor, P G; Huh, T; Kikinis, R; Shenton, M E; Wible, C G

2003-12-01

As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus

Similarity-based search of model organism, disease and drug effect phenotypes

KAUST Repository

Hoehndorf, Robert; Gruenberger, Michael; Gkoutos, Georgios V; Schofield, Paul N

2015-01-01

Background: Semantic similarity measures over phenotype ontologies have been demonstrated to provide a powerful approach for the analysis of model organism phenotypes, the discovery of animal models of human disease, novel pathways, gene functions

Design and Applications of a GeoSemantic Framework for Integration of Data and Model Resources in Hydrologic Systems

Science.gov (United States)

Elag, M.; Kumar, P.

2016-12-01

Hydrologists today have to integrate resources such as data and models, which originate and reside in multiple autonomous and heterogeneous repositories over the Web. Several resource management systems have emerged within geoscience communities for sharing long-tail data, which are collected by individual or small research groups, and long-tail models, which are developed by scientists or small modeling communities. While these systems have increased the availability of resources within geoscience domains, deficiencies remain due to the heterogeneity in the methods, which are used to describe, encode, and publish information about resources over the Web. This heterogeneity limits our ability to access the right information in the right context so that it can be efficiently retrieved and understood without the Hydrologist's mediation. A primary challenge of the Web today is the lack of the semantic interoperability among the massive number of resources, which already exist and are continually being generated at rapid rates. To address this challenge, we have developed a decentralized GeoSemantic (GS) framework, which provides three sets of micro-web services to support (i) semantic annotation of resources, (ii) semantic alignment between the metadata of two resources, and (iii) semantic mediation among Standard Names. Here we present the design of the framework and demonstrate its application for semantic integration between data and models used in the IML-CZO. First we show how the IML-CZO data are annotated using the Semantic Annotation Services. Then we illustrate how the Resource Alignment Services and Knowledge Integration Services are used to create a semantic workflow among TopoFlow model, which is a spatially-distributed hydrologic model and the annotated data. Results of this work are (i) a demonstration of how the GS framework advances the integration of heterogeneous data and models of water-related disciplines by seamless handling of their semantic

Semantic Memory in the Clinical Progression of Alzheimer Disease.

Science.gov (United States)

Tchakoute, Christophe T; Sainani, Kristin L; Henderson, Victor W

2017-09-01

Semantic memory measures may be useful in tracking and predicting progression of Alzheimer disease. We investigated relationships among semantic memory tasks and their 1-year predictive value in women with Alzheimer disease. We conducted secondary analyses of a randomized clinical trial of raloxifene in 42 women with late-onset mild-to-moderate Alzheimer disease. We assessed semantic memory with tests of oral confrontation naming, category fluency, semantic recognition and semantic naming, and semantic density in written narrative discourse. We measured global cognition (Alzheimer Disease Assessment Scale, cognitive subscale), dementia severity (Clinical Dementia Rating sum of boxes), and daily function (Activities of Daily Living Inventory) at baseline and 1 year. At baseline and 1 year, most semantic memory scores correlated highly or moderately with each other and with global cognition, dementia severity, and daily function. Semantic memory task performance at 1 year had worsened one-third to one-half standard deviation. Factor analysis of baseline test scores distinguished processes in semantic and lexical retrieval (semantic recognition, semantic naming, confrontation naming) from processes in lexical search (semantic density, category fluency). The semantic-lexical retrieval factor predicted global cognition at 1 year. Considered separately, baseline confrontation naming and category fluency predicted dementia severity, while semantic recognition and a composite of semantic recognition and semantic naming predicted global cognition. No individual semantic memory test predicted daily function. Semantic-lexical retrieval and lexical search may represent distinct aspects of semantic memory. Semantic memory processes are sensitive to cognitive decline and dementia severity in Alzheimer disease.

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...

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

Hierarchical layered and semantic-based image segmentation using ergodicity map

Science.gov (United States)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects

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...

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.

Language networks associated with computerized semantic indices.

Science.gov (United States)

Pakhomov, Serguei V S; Jones, David T; Knopman, David S

2015-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. Copyright © 2014 Elsevier Inc. All rights reserved.

On the Existence of Semantic Working Memory: Evidence for Direct Semantic Maintenance

Science.gov (United States)

Shivde, Geeta; Anderson, Michael C.

2011-01-01

Despite widespread acknowledgment of the importance of online semantic maintenance, there has been astonishingly little work that clearly establishes this construct. We review the extant work relevant to short-term retention of meaning and show that, although consistent with semantic working memory, most data can be accommodated in other ways.…

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

Modulation of the semantic system by word imageability.

Science.gov (United States)

Sabsevitz, D S; Medler, D A; Seidenberg, M; Binder, J R

2005-08-01

A prevailing neurobiological theory of semantic memory proposes that part of our knowledge about concrete, highly imageable concepts is stored in the form of sensory-motor representations. While this theory predicts differential activation of the semantic system by concrete and abstract words, previous functional imaging studies employing this contrast have provided relatively little supporting evidence. We acquired event-related functional magnetic resonance imaging (fMRI) data while participants performed a semantic similarity judgment task on a large number of concrete and abstract noun triads. Task difficulty was manipulated by varying the degree to which the words in the triad were similar in meaning. Concrete nouns, relative to abstract nouns, produced greater activation in a bilateral network of multimodal and heteromodal association areas, including ventral and medial temporal, posterior-inferior parietal, dorsal prefrontal, and posterior cingulate cortex. In contrast, abstract nouns produced greater activation almost exclusively in the left hemisphere in superior temporal and inferior frontal cortex. Increasing task difficulty modulated activation mainly in attention, working memory, and response monitoring systems, with almost no effect on areas that were modulated by imageability. These data provide critical support for the hypothesis that concrete, imageable concepts activate perceptually based representations not available to abstract concepts. In contrast, processing abstract concepts makes greater demands on left perisylvian phonological and lexical retrieval systems. The findings are compatible with dual coding theory and less consistent with single-code models of conceptual representation. The lack of overlap between imageability and task difficulty effects suggests that once the neural representation of a concept is activated, further maintenance and manipulation of that information in working memory does not further increase neural activation in

Predicting Raters’ Transparency Judgments of English and Chinese Morphological Constituents using Latent Semantic Analysis

Science.gov (United States)

Wang, Hsueh-Cheng; Hsu, Li-Chuan; Tien, Yi-Min; Pomplun, Marc

2013-01-01

The morphological constituents of English compounds (e.g., “butter” and “fly” for “butterfly”) and two-character Chinese compounds may differ in meaning from the whole word. Subjective differences and ambiguity of transparency make the judgments difficult, and a computational alternative based on a general model may be a way to average across subjective differences. The current study proposes two approaches based on Latent Semantic Analysis (Landauer & Dumais, 1997): Model 1 compares the semantic similarity between a compound word and each of its constituents, and Model 2 derives the dominant meaning of a constituent based on a clustering analysis of morphological family members (e.g., “butterfingers” or “buttermilk” for “butter”). The proposed models successfully predicted participants’ transparency ratings, and we recommend that experimenters use Model 1 for English compounds and Model 2 for Chinese compounds, due to raters’ morphological processing in different writing systems. The dominance of lexical meaning, semantic transparency, and the average similarity between all pairs within a morphological family are provided, and practical applications for future studies are discussed. PMID:23784009

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...

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

Behavioural and magnetoencephalographic evidence for the interaction between semantic and episodic memory in healthy elderly subjects.

Science.gov (United States)

La Corte, Valentina; Dalla Barba, Gianfranco; Lemaréchal, Jean-Didier; Garnero, Line; George, Nathalie

2012-10-01

The relationship between episodic and semantic memory systems has long been debated. Some authors argue that episodic memory is contingent on semantic memory (Tulving 1984), while others postulate that both systems are independent since they can be selectively damaged (Squire 1987). The interaction between these memory systems is particularly important in the elderly, since the dissociation of episodic and semantic memory defects characterize different aging-related pathologies. Here, we investigated the interaction between semantic knowledge and episodic memory processes associated with faces in elderly subjects using an experimental paradigm where the semantic encoding of famous and unknown faces was compared to their episodic recognition. Results showed that the level of semantic awareness of items affected the recognition of those items in the episodic memory task. Event-related magnetic fields confirmed this interaction between episodic and semantic memory: ERFs related to the old/new effect during the episodic task were markedly different for famous and unknown faces. The old/new effect for famous faces involved sustained activities maximal over right temporal sensors, showing a spatio-temporal pattern partly similar to that found for famous versus unknown faces during the semantic task. By contrast, an old/new effect for unknown faces was observed on left parieto-occipital sensors. These findings suggest that the episodic memory for famous faces activated the retrieval of stored semantic information, whereas it was based on items' perceptual features for unknown faces. Overall, our results show that semantic information interfered markedly with episodic memory processes and suggested that the neural substrates of these two memory systems overlap.

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.

Gricean Semantics and Vague Speaker-Meaning

OpenAIRE

Schiffer, Stephen

2017-01-01

Presentations of Gricean semantics, including Stephen Neale’s in “Silent Reference,” totally ignore vagueness, even though virtually every utterance is vague. I ask how Gricean semantics might be adjusted to accommodate vague speaker-meaning. My answer is that it can’t accommodate it: the Gricean program collapses in the face of vague speaker-meaning. The Gricean might, however, fi nd some solace in knowing that every other extant meta-semantic and semantic program is in the same boat.

Modeling the Interaction Between Semantic Agents and Semantic Web Services Using MDA Approach

NARCIS (Netherlands)

Kardas, Geylani; Göknil, Arda; Dikenelli, Oguz; Topaloglu, N. Yasemin

2007-01-01

In this paper, we present our metamodeling approach for integrating semantic web services and semantic web enabled agents under Model Driven Architecture (MDA) view which defines a conceptual framework to realize model driven development. We believe that agents must have well designed environment

Care episode retrieval: distributional semantic models for information retrieval in the clinical domain.

Science.gov (United States)

Moen, Hans; Ginter, Filip; Marsi, Erwin; Peltonen, Laura-Maria; Salakoski, Tapio; Salanterä, Sanna

2015-01-01

Patients' health related information is stored in electronic health records (EHRs) by health service providers. These records include sequential documentation of care episodes in the form of clinical notes. EHRs are used throughout the health care sector by professionals, administrators and patients, primarily for clinical purposes, but also for secondary purposes such as decision support and research. The vast amounts of information in EHR systems complicate information management and increase the risk of information overload. Therefore, clinicians and researchers need new tools to manage the information stored in the EHRs. A common use case is, given a--possibly unfinished--care episode, to retrieve the most similar care episodes among the records. This paper presents several methods for information retrieval, focusing on care episode retrieval, based on textual similarity, where similarity is measured through domain-specific modelling of the distributional semantics of words. Models include variants of random indexing and the semantic neural network model word2vec. Two novel methods are introduced that utilize the ICD-10 codes attached to care episodes to better induce domain-specificity in the semantic model. We report on experimental evaluation of care episode retrieval that circumvents the lack of human judgements regarding episode relevance. Results suggest that several of the methods proposed outperform a state-of-the art search engine (Lucene) on the retrieval task.

A Model for Semantic IS Standards

NARCIS (Netherlands)

Folmer, Erwin Johan Albert; Oude Luttighuis, Paul; van Hillegersberg, Jos

2011-01-01

We argue that, in order to suggest improvements of any kind to semantic information system (IS) standards, better understanding of the conceptual structure of semantic IS standard is required. This study develops a model for semantic IS standard, based on literature and expert knowledge. The model

Semantic-based surveillance video retrieval.

Science.gov (United States)

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Episodic, but not semantic, autobiographical memory is reduced in amnestic mild cognitive impairment.

Science.gov (United States)

Murphy, Kelly J; Troyer, Angela K; Levine, Brian; Moscovitch, Morris

2008-11-01

Amnestic mild cognitive impairment (aMCI) is characterized by decline in anterograde memory as measured by the ability to learn and remember new information. We investigated whether retrograde memory for autobiographical information was affected by aMCI. Eighteen control (age 66-84 years) and 17 aMCI (age 66-84 years) participants described a personal event from each of the five periods across the lifespan. These events were transcribed and scored according to procedures that separate episodic (specific happenings) from semantic (general knowledge) elements of autobiographical memory. Although both groups generated protocols of similar length, the composition of autobiographical recall differentiated the groups. The aMCI group protocols were characterized by reduced episodic and increased semantic information relative to the control group. Both groups showed a similar pattern of recall across time periods, with no evidence that the aMCI group had more difficulty recalling recent, rather than remote, life events. These results indicate that episodic and semantic autobiographical memories are differentially affected by the early brain changes associated with aMCI. Reduced autobiographical episodic memories in aMCI may be the result of medial temporal lobe dysfunction, consistent with multiple trace theory, or alternatively, could be related to dysfunction of a wider related network of neocortical structures. In contrast, the preservation of autobiographical semantic memories in aMCI suggests neural systems, such as lateral temporal cortex, that support these memories, may remain relatively intact.

Semantic models for adaptive interactive systems

CERN Document Server

Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

2013-01-01

Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

Some Novel Techniques in Operational Semantics

DEFF Research Database (Denmark)

Mosses, Peter David

2003-01-01

Several novel techniques for use in operational semantics are presented. They were developed in connection with a modular vatriant of the conventional Structural Operational Semantics framework, but can also be exploited when modularity is of no great concern. Gives a simple introduction to the m......Several novel techniques for use in operational semantics are presented. They were developed in connection with a modular vatriant of the conventional Structural Operational Semantics framework, but can also be exploited when modularity is of no great concern. Gives a simple introduction...

A behavioral similarity measure between labeled Petri nets based on principal transition sequences

NARCIS (Netherlands)

Wang, J.; He, T.; Wen, L.; Wu, N.; Hofstede, ter A.H.M.; Su, J.; Meersman, R.; Dillon, T.S.; Herrero, P.

2010-01-01

Being able to determine the degree of similarity between process models is important for management, reuse, and analysis of business process models. In this paper we propose a novel method to determine the degree of similarity between process models, which exploits their semantics. Our approach is

Characteristics of gray matter morphological change in Parkinson's disease patients with semantic abstract reasoning deficits.

Science.gov (United States)

Wang, Li; Nie, Kun; Zhao, Xin; Feng, Shujun; Xie, Sifen; He, Xuetao; Ma, Guixian; Wang, Limin; Huang, Zhiheng; Huang, Biao; Zhang, Yuhu; Wang, Lijuan

2018-04-23

Semantic abstract reasoning(SAR) is an important executive domain that is involved in semantic information processing and enables one to make sense of the attributes of objects, facts and concepts in the world. We sought to investigate whether Parkinson's disease subjects(PDs) have difficulty in SAR and to examine the associated pattern of gray matter morphological changes. Eighty-six PDs and 30 healthy controls were enrolled. PDs were grouped into PD subjects with Similarities preservation(PDSP, n = 62) and PD subjects with Similarities impairment(PDSI, n = 24)according to their performance on the Similarities subtest of the Wechsler Adult Intelligence Scale. Brain structural images were captured with a 3T MRI scanner. Surface-based investigation of cortical thickness and automated segmentation of deep gray matter were conducted using FreeSurfer software. PDs performed notably worse on the Similarities test than controls(F = 13.56, P < 0.001).In the PDSI group, cortical thinning associated with Similarities scores was found in the left superior frontal, left superior parietal and left rostral middle frontal regions. Notable atrophy of the bilateral hippocampi was observed, but only the right hippocampus volume was positively correlated with the Similarities scores of the PDSI group. PDs have difficulty in SAR, and this limitation may be associated with impaired conceptual abstraction and generalization along with semantic memory deficits. Cortical thinning in the left frontal and parietal regions and atrophy in the right hippocampus may explain these impairments among Chinese PDs. Copyright © 2017 Elsevier B.V. All rights reserved.

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)

Episodic, generalized, and semantic memory tests: switching and strength effects.

Science.gov (United States)

Humphreys, Michael S; Murray, Krista L

2011-09-01

We continue the process of investigating the probabilistic paired associate paradigm in an effort to understand the memory access control processes involved and to determine whether the memory structure produced is in transition between episodic and semantic memory. In this paradigm two targets are probabilistically paired with a cue across a large number of short lists. Participants can recall the target paired with the cue in the most recent list (list specific test), produce the first of the two targets that have been paired with that cue to come to mind (generalised test), and produce a free association response (semantic test). Switching between a generalised test and a list specific test did not produce a switching cost indicating a general similarity in the control processes involved. In addition, there was evidence for a dissociation between two different strength manipulations (amount of study time and number of cue-target pairings) such that number of pairings influenced the list specific, generalised and the semantic test but amount of study time only influenced the list specific and generalised test. © 2011 Canadian Psychological Association

Social Semantics for an Effective Enterprise

Science.gov (United States)

Berndt, Sarah; Doane, Mike

2012-01-01

An evolution of the Semantic Web, the Social Semantic Web (s2w), facilitates knowledge sharing with "useful information based on human contributions, which gets better as more people participate." The s2w reaches beyond the search box to move us from a collection of hyperlinked facts, to meaningful, real time context. When focused through the lens of Enterprise Search, the Social Semantic Web facilitates the fluid transition of meaningful business information from the source to the user. It is the confluence of human thought and computer processing structured with the iterative application of taxonomies, folksonomies, ontologies, and metadata schemas. The importance and nuances of human interaction are often deemphasized when focusing on automatic generation of semantic markup, which results in dissatisfied users and unrealized return on investment. Users consistently qualify the value of information sets through the act of selection, making them the de facto stakeholders of the Social Semantic Web. Employers are the ultimate beneficiaries of s2w utilization with a better informed, more decisive workforce; one not achieved with an IT miracle technology, but by improved human-computer interactions. Johnson Space Center Taxonomist Sarah Berndt and Mike Doane, principal owner of Term Management, LLC discuss the planning, development, and maintenance stages for components of a semantic system while emphasizing the necessity of a Social Semantic Web for the Enterprise. Identification of risks and variables associated with layering the successful implementation of a semantic system are also modeled.

Predicting survey responses: how and why semantics shape survey statistics on organizational behaviour.

Directory of Open Access Journals (Sweden)

Jan Ketil Arnulf

Full Text Available Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60-86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain.

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...

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction

OpenAIRE

Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A.; Barak, Ohr; Lambon Ralph, Matthew; Jefferies, Elizabeth

2018-01-01

Semantic cognition, as described by the Controlled Semantic Cognition (CSC) framework (Rogers, Patterson, Jefferies, & Lambon Ralph, 2015), involves two key components: activation of coherent, generalizable concepts within a heteromodal ‘hub’ in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task- appropriate behaviour. Executive-semantic goal representations, largely supported by executive...

A Semantic Middleware Architecture Focused on Data and Heterogeneity Management within the Smart Grid

Directory of Open Access Journals (Sweden)

Rubén de Diego

2014-09-01

Full Text Available There is an increasing tendency of turning the current power grid, essentially unaware of variations in electricity demand and scattered energy sources, into something capable of bringing a degree of intelligence by using tools strongly related to information and communication technologies, thus turning into the so-called Smart Grid. In fact, it could be considered that the Smart Grid is an extensive smart system that spreads throughout any area where power is required, providing a significant optimization in energy generation, storage and consumption. However, the information that must be treated to accomplish these tasks is challenging both in terms of complexity (semantic features, distributed systems, suitable hardware and quantity (consumption data, generation data, forecasting functionalities, service reporting, since the different energy beneficiaries are prone to be heterogeneous, as the nature of their own activities is. This paper presents a proposal on how to deal with these issues by using a semantic middleware architecture that integrates different components focused on specific tasks, and how it is used to handle information at every level and satisfy end user requests.

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.

Jigsaw Semantics

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Paul J. E. Dekker

2010-12-01

Full Text Available In the last decade the enterprise of formal semantics has been under attack from several philosophical and linguistic perspectives, and it has certainly suffered from its own scattered state, which hosts quite a variety of paradigms which may seem to be incompatible. It will not do to try and answer the arguments of the critics, because the arguments are often well-taken. The negative conclusions, however, I believe are not. The only adequate reply seems to be a constructive one, which puts several pieces of formal semantics, in particular dynamic semantics, together again. In this paper I will try and sketch an overview of tasks, techniques, and results, which serves to at least suggest that it is possible to develop a coherent overall picture of undeniably important and structural phenomena in the interpretation of natural language. The idea is that the concept of meanings as truth conditions after all provides an excellent start for an integrated study of the meaning and use of natural language, and that an extended notion of goal directed pragmatics naturally complements this picture. None of the results reported here are really new, but we think it is important to re-collect them.ReferencesAsher, Nicholas & Lascarides, Alex. 1998. ‘Questions in Dialogue’. Linguistics and Philosophy 23: 237–309.http://dx.doi.org/10.1023/A:1005364332007Borg, Emma. 2007. ‘Minimalism versus contextualism in semantics’. In Gerhard Preyer & Georg Peter (eds. ‘Context-Sensitivity and Semantic Minimalism’, pp. 339–359. Oxford: Oxford University Press.Cappelen, Herman & Lepore, Ernest. 1997. ‘On an Alleged Connection between Indirect Quotation and Semantic Theory’. Mind and Language 12: pp. 278–296.Cappelen, Herman & Lepore, Ernie. 2005. Insensitive Semantics. Oxford: Blackwell.http://dx.doi.org/10.1002/9780470755792Dekker, Paul. 2002. ‘Meaning and Use of Indefinite Expressions’. Journal of Logic, Language and Information 11: pp. 141–194

Semantic tagging of and semantic enhancements to systematics papers: ZooKeys working examples

NARCIS (Netherlands)

Penev, L.; Agosti, D.; Georgiev, T.; Catapano, T.; Miller, J.; Blagoderov, V.; Roberts, D.; Smith, V.S.; Brake, I.; Ryrcroft, S.; Scott, B.; Johnson, N.F.; Morris, R.A.; Sautter, G.; Chavan, V.; Robertson, T.; Remsen, D.; Stoev, P.; Parr, C.; Knapp, S.; Kress, W.J.; Thompson, F.C.; Erwin, T.

2010-01-01

The concept of semantic tagging and its potential for semantic enhancements to taxonomic papers is outlined and illustrated by four exemplar papers published in the present issue of ZooKeys. The four papers were created in different ways: (i) written in Microsoft Word and submitted as non-tagged

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...

Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks

OpenAIRE

Zhelezniak, Vitalii; Busbridge, Dan; Shen, April; Smith, Samuel L.; Hammerla, Nils Y.

2018-01-01

Experimental evidence indicates that simple models outperform complex deep networks on many unsupervised similarity tasks. We provide a simple yet rigorous explanation for this behaviour by introducing the concept of an optimal representation space, in which semantically close symbols are mapped to representations that are close under a similarity measure induced by the model's objective function. In addition, we present a straightforward procedure that, without any retraining or architectura...

Music training and semantic clustering in college students.

Science.gov (United States)

Hogan, David E; Huesman, Thomas

2008-12-01

College students with 5 or more years of music training recalled significantly more words from a 16-item word list than did students with 0-4 years of training. The superior recall of the extensively trained students linked to better application of a semantic-clustering strategy across a series of 3 test trials. Music education and language experience may have similar influences on the development of verbal memory.

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2008-01-01

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...

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

Science.gov (United States)

Willoughby, Karen A; Desrocher, Mary; Levine, Brian; Rovet, Joanne F

2012-01-01

Few studies have examined both episodic and semantic autobiographical memory (AM) performance during late childhood and early adolescence. Using the newly developed Children's Autobiographical Interview (CAI), the present study examined the effects of age and sex on episodic and semantic AM and everyday memory in 182 children and adolescents. Results indicated that episodic and semantic AM both improved between 8 and 16 years of age; however, age-related changes were larger for episodic AM than for semantic AM. In addition, females were found to recall more episodic AM details, but not more semantic AM details, than males. Importantly, this sex difference in episodic AM recall was attenuated under conditions of high retrieval support (i.e., the use of probing questions). The ability to clearly visualize past events at the time of recollection was related to children's episodic AM recall performance, particularly the retrieval of perceptual details. Finally, similar age and sex effects were found between episodic AM and everyday memory ability (e.g., memory for everyday activities). More specifically, older participants and females exhibited better episodic AM and everyday memory performance than younger participants and males. Overall, the present study provides important new insight into both episodic and semantic AM performance, as well as the relation between episodic AM and everyday memory, during late childhood and adolescence.

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

Science.gov (United States)

Willoughby, Karen A.; Desrocher, Mary; Levine, Brian; Rovet, Joanne F.

2012-01-01

Few studies have examined both episodic and semantic autobiographical memory (AM) performance during late childhood and early adolescence. Using the newly developed Children’s Autobiographical Interview (CAI), the present study examined the effects of age and sex on episodic and semantic AM and everyday memory in 182 children and adolescents. Results indicated that episodic and semantic AM both improved between 8 and 16 years of age; however, age-related changes were larger for episodic AM than for semantic AM. In addition, females were found to recall more episodic AM details, but not more semantic AM details, than males. Importantly, this sex difference in episodic AM recall was attenuated under conditions of high retrieval support (i.e., the use of probing questions). The ability to clearly visualize past events at the time of recollection was related to children’s episodic AM recall performance, particularly the retrieval of perceptual details. Finally, similar age and sex effects were found between episodic AM and everyday memory ability (e.g., memory for everyday activities). More specifically, older participants and females exhibited better episodic AM and everyday memory performance than younger participants and males. Overall, the present study provides important new insight into both episodic and semantic AM performance, as well as the relation between episodic AM and everyday memory, during late childhood and adolescence. PMID:22403560

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction

OpenAIRE

Thompson, Hannah; Almaghyuli, Azizah; Noonan, Krist A.; barak, Ohr; Lambon Ralph, Matthew A.; Jefferies, Elizabeth

2018-01-01

Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., 2015, Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal ‘hub’ in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive–semantic goal representations, largely supported by executive regions ...

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.

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)

Neural correlates underlying musical semantic memory.

Science.gov (United States)

Groussard, M; Viader, F; Landeau, B; Desgranges, B; Eustache, F; Platel, H

2009-07-01

Numerous functional imaging studies have examined the neural basis of semantic memory mainly using verbal and visuospatial materials. Musical material also allows an original way to explore semantic memory processes. We used PET imaging to determine the neural substrates that underlie musical semantic memory using different tasks and stimuli. The results of three PET studies revealed a greater involvement of the anterior part of the temporal lobe. Concerning clinical observations and our neuroimaging data, the musical lexicon (and most widely musical semantic memory) appears to be sustained by a temporo-prefrontal cerebral network involving right and left cerebral regions.

Is semantic priming due to association strength or feature overlap? A microanalytic review.

Science.gov (United States)

Hutchison, Keith A

2003-12-01

In a recent meta-analysis, Lucas (2000) concluded that there is strong evidence of an overall pure semantic priming effect but no evidence of priming based purely on association. In the present review, I critically examine the individual studies claiming evidence of featural and associative relations in semantic memory. The most important conclusion is that automatic priming appears to be due to both association strength and feature overlap. Mediated associates provide the strongest evidence of automatic associative priming, whereas functional associates, synonyms, and antonyms instead support priming based on feature overlap. In contrast, automatic priming does not occur for category coordinates or perceptually similar items, at least when presented in the visual modality. The status of other relations, such as collocates, episodic relatives, and script relations, is unclear and requires further experimentation. Implications for current models of semantic representation and priming are discussed.

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

Directory of Open Access Journals (Sweden)

Cody eTousignant

2012-03-01

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

Semantics, pragmatics, and formal thought disorders in people with schizophrenia.

Science.gov (United States)

Salavera, Carlos; Puyuelo, Miguel; Antoñanzas, José L; Teruel, Pilar

2013-01-01

The aim of this study was to analyze how formal thought disorders (FTD) affect semantics and pragmatics in patients with schizophrenia. The sample comprised subjects with schizophrenia (n = 102) who met the criteria for the disorder according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition Text Revision. In the research process, the following scales were used: Positive and Negative Syndrome Scale (PANSS) for psychopathology measurements; the Scale for the Assessment of Thought, Language, and Communication (TLC) for FTD, Word Accentuation Test (WAT), System for the Behavioral Evaluation of Social Skills (SECHS), the pragmatics section of the Objective Criteria Language Battery (BLOC-SR) and the verbal sections of the Wechsler Adults Intelligence Scale (WAIS) III, for assessment of semantics and pragmatics. The results in the semantics and pragmatics sections were inferior to the average values obtained in the general population. Our data demonstrated that the more serious the FTD, the worse the performances in the Verbal-WAIS tests (particularly in its vocabulary, similarities, and comprehension sections), SECHS, and BLOC-SR, indicating that FTD affects semantics and pragmatics, although the results of the WAT indicated good premorbid language skills. The principal conclusion we can draw from this study is the evidence that in schizophrenia the superior level of language structure seems to be compromised, and that this level is related to semantics and pragmatics; when there is an alteration in this level, symptoms of FTD appear, with a wide-ranging relationship between both language and FTD. The second conclusion is that the subject's language is affected by the disorder and rules out the possibility of a previous verbal impairment.

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...

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2010-01-01

We present a new abstract machine for Abadi and Cardelli's untyped non-imperative calculus of objects.  This abstract machine mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i.e., big-step operational semantics) specified...

CASL - The CoFI Algebraic Specification Language - Semantics

DEFF Research Database (Denmark)

Haxthausen, Anne

1999-01-01

This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the second complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop in Amsterdam in March 1999.......This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the second complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop in Amsterdam in March 1999....

Challenges as enablers for high quality Linked Data: insights from the Semantic Publishing Challenge

Directory of Open Access Journals (Sweden)

Anastasia Dimou

2017-01-01

Full Text Available While most challenges organized so far in the Semantic Web domain are focused on comparing tools with respect to different criteria such as their features and competencies, or exploiting semantically enriched data, the Semantic Web Evaluation Challenges series, co-located with the ESWC Semantic Web Conference, aims to compare them based on their output, namely the produced dataset. The Semantic Publishing Challenge is one of these challenges. Its goal is to involve participants in extracting data from heterogeneous sources on scholarly publications, and producing Linked Data that can be exploited by the community itself. This paper reviews lessons learned from both (i the overall organization of the Semantic Publishing Challenge, regarding the definition of the tasks, building the input dataset and forming the evaluation, and (ii the results produced by the participants, regarding the proposed approaches, the used tools, the preferred vocabularies and the results produced in the three editions of 2014, 2015 and 2016. We compared these lessons to other Semantic Web Evaluation Challenges. In this paper, we (i distill best practices for organizing such challenges that could be applied to similar events, and (ii report observations on Linked Data publishing derived from the submitted solutions. We conclude that higher quality may be achieved when Linked Data is produced as a result of a challenge, because the competition becomes an incentive, while solutions become better with respect to Linked Data publishing best practices when they are evaluated against the rules of the  challenge.

Differential Medial Temporal Lobe and Parietal Cortical Contributions to Real-world Autobiographical Episodic and Autobiographical Semantic Memory.

Science.gov (United States)

Brown, Thackery I; Rissman, Jesse; Chow, Tiffany E; Uncapher, Melina R; Wagner, Anthony D

2018-04-18

Autobiographical remembering can depend on two forms of memory: episodic (event) memory and autobiographical semantic memory (remembering personally relevant semantic knowledge, independent of recalling a specific experience). There is debate about the degree to which the neural signals that support episodic recollection relate to or build upon autobiographical semantic remembering. Pooling data from two fMRI studies of memory for real-world personal events, we investigated whether medial temporal lobe (MTL) and parietal subregions contribute to autobiographical episodic and semantic remembering. During scanning, participants made memory judgments about photograph sequences depicting past events from their life or from others' lives, and indicated whether memory was based on episodic or semantic knowledge. Results revealed several distinct functional patterns: activity in most MTL subregions was selectively associated with autobiographical episodic memory; the hippocampal tail, superior parietal lobule, and intraparietal sulcus were similarly engaged when memory was based on retrieval of an autobiographical episode or autobiographical semantic knowledge; and angular gyrus demonstrated a graded pattern, with activity declining from autobiographical recollection to autobiographical semantic remembering to correct rejections of novel events. Collectively, our data offer insights into MTL and parietal cortex functional organization, and elucidate circuitry that supports different forms of real-world autobiographical memory.

Using semantic analysis to improve speech recognition performance

OpenAIRE

Erdoğan, Hakan; Erdogan, Hakan; Sarıkaya, Ruhi; Sarikaya, Ruhi; Chen, Stanley F.; Gao, Yuqing; Picheny, Michael

2005-01-01

Although syntactic structure has been used in recent work in language modeling, there has not been much effort in using semantic analysis for language models. In this study, we propose three new language modeling techniques that use semantic analysis for spoken dialog systems. We call these methods concept sequence modeling, two-level semantic-lexical modeling, and joint semantic-lexical modeling. These models combine lexical information with varying amounts of semantic information, using ann...

Co-clustering for Weblogs in Semantic Space

DEFF Research Database (Denmark)

Zong, Yu; Xu, Guandong; Dolog, Peter

2010-01-01

Web clustering is an approach for aggregating web objects into various groups according to underlying relationships among them. Finding co-clusters of web objects in semantic space is an interesting topic in the context of web usage mining, which is able to capture the underlying user navigational...... interest and content preference simultaneously. In this paper we will present a novel web co-clustering algorithm named Co-Clustering in Semantic space (COCS) to simultaneously partition web users and pages via a latent semantic analysis approach. In COCS, we first, train the latent semantic space...... of weblog data by using Probabilistic Latent Semantic Analysis (PLSA) model, and then, project all weblog data objects into this semantic space with probability distribution to capture the relationship among web pages and web users, at last, propose a clustering algorithm to generate the co...

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...

Action representation: crosstalk between semantics and pragmatics.

Science.gov (United States)

Prinz, Wolfgang

2014-03-01

Marc Jeannerod pioneered a representational approach to movement and action. In his approach, motor representations provide both, declarative knowledge about action and procedural knowledge for action (action semantics and action pragmatics, respectively). Recent evidence from language comprehension and action simulation supports the claim that action pragmatics and action semantics draw on common representational resources, thus challenging the traditional divide between declarative and procedural action knowledge. To account for these observations, three kinds of theoretical frameworks are discussed: (i) semantics is grounded in pragmatics, (ii) pragmatics is anchored in semantics, and (iii) pragmatics is part and parcel of semantics. © 2013 Elsevier Ltd. All rights reserved.

A Semantic Analysis Method for Scientific and Engineering Code

Science.gov (United States)

Stewart, Mark E. M.

1998-01-01

This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

Phonological, visual, and semantic coding strategies and children's short-term picture memory span

OpenAIRE

Henry, L.; Messer, D. J.; Luger-Klein, S.; Crane, L.

2012-01-01

Three experiments addressed controversies in the previous literature on the development of phonological and other forms of short-term memory coding in children, using assessments of picture memory span that ruled out potentially confounding effects of verbal input and output. Picture materials were varied in terms of phonological similarity, visual similarity, semantic similarity, and word length. Older children (6/8-year-olds), but not younger children (4/5-year-olds), demonstrated robust an...

The Semantics of Plurals: A Defense of Singularism

Science.gov (United States)

Florio, Salvatore

2010-01-01

In this dissertation, I defend "semantic singularism", which is the view that syntactically plural terms, such as "they" or "Russell and Whitehead", are semantically singular. A semantically singular term is a term that denotes a single entity. Semantic singularism is to be distinguished from "syntactic singularism", according to which…

Towards a Reactive Semantic Execution Environment

Science.gov (United States)

Komazec, Srdjan; Facca, Federico Michele

Managing complex and distributed software systems built on top of the service-oriented paradigm has never been more challenging. While Semantic Web Service technologies offer a promising set of languages and tools as a foundation to resolve the heterogeneity and scalability issues, they are still failing to provide an autonomic execution environment. In this paper we present an approach based on Semantic Web Services to enable the monitoring and self-management of a Semantic Execution Environment (SEE), a brokerage system for Semantic Web Services. Our approach is founded on the event-triggered reactivity paradigm in order to facilitate environment control, thus contributing to its autonomicity, robustness and flexibility.

Linking Disparate Datasets of the Earth Sciences with the SemantEco Annotator

Science.gov (United States)

Seyed, P.; Chastain, K.; McGuinness, D. L.

2013-12-01

library of vocabularies to assist the user in locating terms to describe observed entities, their properties, and relationships. The Annotator leverages vocabulary definitions of these concepts to guide the user in describing data in a logically consistent manner. The vocabularies made available through the Annotator are open, as is the Annotator itself. We have taken a step towards making semantic annotation/translation of data more accessible. Our vision for the Annotator is as a tool that can be integrated into a semantic data 'workbench' environment, which would allow semantic annotation of a variety of data formats, using standard vocabularies. These vocabularies involved enable search for similar datasets, and integration with any semantically-enabled applications for analysis and visualization.

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.

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.

Life, Information, Entropy, and Time: Vehicles for Semantic Inheritance.

Science.gov (United States)

Crofts, Antony R

2007-01-01

Attempts to understand how information content can be included in an accounting of the energy flux of the biosphere have led to the conclusion that, in information transmission, one component, the semantic content, or "the meaning of the message," adds no thermodynamic burden over and above costs arising from coding, transmission and translation. In biology, semantic content has two major roles. For all life forms, the message of the genotype encoded in DNA specifies the phenotype, and hence the organism that is tested against the real world through the mechanisms of Darwinian evolution. For human beings, communication through language and similar abstractions provides an additional supra-phenotypic vehicle for semantic inheritance, which supports the cultural heritages around which civilizations revolve. The following three postulates provide the basis for discussion of a number of themes that demonstrate some important consequences. (i) Information transmission through either pathway has thermodynamic components associated with data storage and transmission. (ii) The semantic content adds no additional thermodynamic cost. (iii) For all semantic exchange, meaning is accessible only through translation and interpretation, and has a value only in context. (1) For both pathways of semantic inheritance, translational and copying machineries are imperfect. As a consequence both pathways are subject to mutation and to evolutionary pressure by selection. Recognition of semantic content as a common component allows an understanding of the relationship between genes and memes, and a reformulation of Universal Darwinism. (2) The emergent properties of life are dependent on a processing of semantic content. The translational steps allow amplification in complexity through combinatorial possibilities in space and time. Amplification depends on the increased potential for complexity opened by 3D interaction specificity of proteins, and on the selection of useful variants by

The paca that roared: Immediate cumulative semantic interference among newly acquired words.

Science.gov (United States)

Oppenheim, Gary M

2018-08-01

With 40,000 words in the average vocabulary, how can speakers find the specific words that they want so quickly and easily? Cumulative semantic interference in language production provides a clue: when naming a large series of pictures, with a few mammals sprinkled about, naming each subsequent mammal becomes slower and more error-prone. Such interference mirrors predictions from an incremental learning algorithm applied to meaning-driven retrieval from an established vocabulary, suggesting retrieval benefits from a constant, implicit, re-optimization process (Oppenheim et al., 2010). But how quickly would a new mammal (e.g. paca) engage in this re-optimization? In this experiment, 18 participants studied 3 novel and 3 familiar exemplars from each of six semantic categories, and immediately performed a timed picture-naming task. Consistent with the learning model's predictions, naming latencies revealed immediate cumulative semantic interference in all directions: from new words to new words, from new words to old words, from old words to new words, and from old words to old words. Repeating the procedure several days later produced similar-magnitude effects, demonstrating that newly acquired words can be immediately semantically integrated, at least to the extent necessary to produce typical cumulative semantic interference. These findings extend the Dark Side model's scope to include novel word production, and are considered in terms of mechanisms for lexical selection. Copyright © 2018 Elsevier B.V. All rights reserved.

The roles of scene gist and spatial dependency among objects in the semantic guidance of attention in real-world scenes.

Science.gov (United States)

Wu, Chia-Chien; Wang, Hsueh-Cheng; Pomplun, Marc

2014-12-01

A previous study (Vision Research 51 (2011) 1192-1205) found evidence for semantic guidance of visual attention during the inspection of real-world scenes, i.e., an influence of semantic relationships among scene objects on overt shifts of attention. In particular, the results revealed an observer bias toward gaze transitions between semantically similar objects. However, this effect is not necessarily indicative of semantic processing of individual objects but may be mediated by knowledge of the scene gist, which does not require object recognition, or by known spatial dependency among objects. To examine the mechanisms underlying semantic guidance, in the present study, participants were asked to view a series of displays with the scene gist excluded and spatial dependency varied. Our results show that spatial dependency among objects seems to be sufficient to induce semantic guidance. Scene gist, on the other hand, does not seem to affect how observers use semantic information to guide attention while viewing natural scenes. Extracting semantic information mainly based on spatial dependency may be an efficient strategy of the visual system that only adds little cognitive load to the viewing task. Copyright © 2014 Elsevier Ltd. All rights reserved.

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)

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.

Localizing semantic interference from distractor sounds in picture naming: A dual-task study.

Science.gov (United States)

Mädebach, Andreas; Kieseler, Marie-Luise; Jescheniak, Jörg D

2017-10-13

In this study we explored the locus of semantic interference in a novel picture-sound interference task in which participants name pictures while ignoring environmental distractor sounds. In a previous study using this task (Mädebach, Wöhner, Kieseler, & Jescheniak, in Journal of Experimental Psychology: Human Perception and Performance, 43, 1629-1646, 2017), we showed that semantically related distractor sounds (e.g., BARKING dog ) interfere with a picture-naming response (e.g., "horse") more strongly than unrelated distractor sounds do (e.g., DRUMMING drum ). In the experiment reported here, we employed the psychological refractory period (PRP) approach to explore the locus of this effect. We combined a geometric form classification task (square vs. circle; Task 1) with the picture-sound interference task (Task 2). The stimulus onset asynchrony (SOA) between the tasks was systematically varied (0 vs. 500 ms). There were three central findings. First, the semantic interference effect from distractor sounds was replicated. Second, picture naming (in Task 2) was slower with the short than with the long task SOA. Third, both effects were additive-that is, the semantic interference effects were of similar magnitude at both task SOAs. This suggests that the interference arises during response selection or later stages, not during early perceptual processing. This finding corroborates the theory that semantic interference from distractor sounds reflects a competitive selection mechanism in word production.

Phonological similarity in working memory span tasks.

Science.gov (United States)

Chow, Michael; Macnamara, Brooke N; Conway, Andrew R A

2016-08-01

In a series of four experiments, we explored what conditions are sufficient to produce a phonological similarity facilitation effect in working memory span tasks. By using the same set of memoranda, but differing the secondary-task requirements across experiments, we showed that a phonological similarity facilitation effect is dependent upon the semantic relationship between the memoranda and the secondary-task stimuli, and is robust to changes in the representation, ordering, and pool size of the secondary-task stimuli. These findings are consistent with interference accounts of memory (Brown, Neath, & Chater, Psychological Review, 114, 539-576, 2007; Oberauer, Lewandowsky, Farrell, Jarrold, & Greaves, Psychonomic Bulletin & Review, 19, 779-819, 2012), whereby rhyming stimuli provide a form of categorical similarity that allows distractors to be excluded from retrieval at recall.

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.

Hippocampal activation during episodic and semantic memory retrieval: comparing category production and category cued recall.

Science.gov (United States)

Ryan, Lee; Cox, Christine; Hayes, Scott M; Nadel, Lynn

2008-01-01

Whether or not the hippocampus participates in semantic memory retrieval has been the focus of much debate in the literature. However, few neuroimaging studies have directly compared hippocampal activation during semantic and episodic retrieval tasks that are well matched in all respects other than the source of the retrieved information. In Experiment 1, we compared hippocampal fMRI activation during a classic semantic memory task, category production, and an episodic version of the same task, category cued recall. Left hippocampal activation was observed in both episodic and semantic conditions, although other regions of the brain clearly distinguished the two tasks. Interestingly, participants reported using retrieval strategies during the semantic retrieval task that relied on autobiographical and spatial information; for example, visualizing themselves in their kitchen while producing items for the category kitchen utensils. In Experiment 2, we considered whether the use of these spatial and autobiographical retrieval strategies could have accounted for the hippocampal activation observed in Experiment 1. Categories were presented that elicited one of three retrieval strategy types, autobiographical and spatial, autobiographical and nonspatial, and neither autobiographical nor spatial. Once again, similar hippocampal activation was observed for all three category types, regardless of the inclusion of spatial or autobiographical content. We conclude that the distinction between semantic and episodic memory is more complex than classic memory models suggest.

An explicit semantic relatedness measure based on random walk

Directory of Open Access Journals (Sweden)

HU Sihui

2016-10-01

Full Text Available The semantic relatedness calculation of open domain knowledge network is a significant issue.In this paper,pheromone strategy is drawn from the thought of ant colony algorithm and is integrated into the random walk which is taken as the basic framework of calculating the semantic relatedness degree.The pheromone distribution is taken as a criterion of determining the tightness degree of semantic relatedness.A method of calculating semantic relatedness degree based on random walk is proposed and the exploration process of calculating the semantic relatedness degree is presented in a dominant way.The method mainly contains Path Select Model(PSM and Semantic Relatedness Computing Model(SRCM.PSM is used to simulate the path selection of ants and pheromone release.SRCM is used to calculate the semantic relatedness by utilizing the information returned by ants.The result indicates that the method could complete semantic relatedness calculation in linear complexity and extend the feasible strategy of semantic relatedness calculation.

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-07-01

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

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

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.

Semantic e-Learning: Next Generation of e-Learning?

Science.gov (United States)

Konstantinos, Markellos; Penelope, Markellou; Giannis, Koutsonikos; Aglaia, Liopa-Tsakalidi

Semantic e-learning aspires to be the next generation of e-learning, since the understanding of learning materials and knowledge semantics allows their advanced representation, manipulation, sharing, exchange and reuse and ultimately promote efficient online experiences for users. In this context, the paper firstly explores some fundamental Semantic Web technologies and then discusses current and potential applications of these technologies in e-learning domain, namely, Semantic portals, Semantic search, personalization, recommendation systems, social software and Web 2.0 tools. Finally, it highlights future research directions and open issues of the field.

Explaining Semantic Short-Term Memory Deficits: Evidence for the Critical Role of Semantic Control

Science.gov (United States)

Hoffman, Paul; Jefferies, Elizabeth; Lambon Ralph, Matthew A.

2011-01-01

Patients with apparently selective short-term memory (STM) deficits for semantic information have played an important role in developing multi-store theories of STM and challenge the idea that verbal STM is supported by maintaining activation in the language system. We propose that semantic STM deficits are not as selective as previously thought…

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...

A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

OpenAIRE

Hamed Hassanzadeh; MohammadReza Keyvanpour

2011-01-01

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as ...

Processing lexical semantic and syntactic information in first and second language: fMRI evidence from German and Russian.

Science.gov (United States)

Rüschemeyer, Shirley-Ann; Fiebach, Christian J; Kempe, Vera; Friederici, Angela D

2005-06-01

We introduce two experiments that explored syntactic and semantic processing of spoken sentences by native and non-native speakers. In the first experiment, the neural substrates corresponding to detection of syntactic and semantic violations were determined in native speakers of two typologically different languages using functional magnetic resonance imaging (fMRI). The results show that the underlying neural response of participants to stimuli across different native languages is quite similar. In the second experiment, we investigated how non-native speakers of a language process the same stimuli presented in the first experiment. First, the results show a more similar pattern of increased activation between native and non-native speakers in response to semantic violations than to syntactic violations. Second, the non-native speakers were observed to employ specific portions of the frontotemporal language network differently from those employed by native speakers. These regions included the inferior frontal gyrus (IFG), superior temporal gyrus (STG), and subcortical structures of the basal ganglia.

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)

Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms.

Science.gov (United States)

Falda, Marco; Toppo, Stefano; Pescarolo, Alessandro; Lavezzo, Enrico; Di Camillo, Barbara; Facchinetti, Andrea; Cilia, Elisa; Velasco, Riccardo; Fontana, Paolo

2012-03-28

Predicting protein function has become increasingly demanding in the era of next generation sequencing technology. The task to assign a curator-reviewed function to every single sequence is impracticable. Bioinformatics tools, easy to use and able to provide automatic and reliable annotations at a genomic scale, are necessary and urgent. In this scenario, the Gene Ontology has provided the means to standardize the annotation classification with a structured vocabulary which can be easily exploited by computational methods. Argot2 is a web-based function prediction tool able to annotate nucleic or protein sequences from small datasets up to entire genomes. It accepts as input a list of sequences in FASTA format, which are processed using BLAST and HMMER searches vs UniProKB and Pfam databases respectively; these sequences are then annotated with GO terms retrieved from the UniProtKB-GOA database and the terms are weighted using the e-values from BLAST and HMMER. The weighted GO terms are processed according to both their semantic similarity relations described by the Gene Ontology and their associated score. The algorithm is based on the original idea developed in a previous tool called Argot. The entire engine has been completely rewritten to improve both accuracy and computational efficiency, thus allowing for the annotation of complete genomes. The revised algorithm has been already employed and successfully tested during in-house genome projects of grape and apple, and has proven to have a high precision and recall in all our benchmark conditions. It has also been successfully compared with Blast2GO, one of the methods most commonly employed for sequence annotation. The server is freely accessible at http://www.medcomp.medicina.unipd.it/Argot2.

Information Interaction as a Mechanism of Semantic Gap Elimination

Directory of Open Access Journals (Sweden)

Victor Y. Tsvetkov

2013-01-01

Full Text Available The article studies semantic gap as an objective phenomenon, shows that semantic gap occurs both in parallel computing and in other areas. Semantic description of the content is revealed as a set of different descriptions. Causes of semantic gap are described. The content of information exchange is explained in the article. Information interaction in the semantic field is interpreted as a mechanism to lessen the gap

On the (un)suitability of semantic categories

DEFF Research Database (Denmark)

Rijkhoff, Jan

2009-01-01

Since Greenberg’s groundbreaking publication on universals of grammar, typologists have used semantic categories to investigate (constraints on) morphological and syntactic variation in the world’s languages and this tradition has been continued in the WALS project. It is argued here that the emp......Since Greenberg’s groundbreaking publication on universals of grammar, typologists have used semantic categories to investigate (constraints on) morphological and syntactic variation in the world’s languages and this tradition has been continued in the WALS project. It is argued here...... that the employment of semantic categories has some serious drawbacks, however, suggesting that semantic categories, just like formal categories, cannot be equated across languages in morphosyntactic typology. Whereas formal categories are too narrow in that they do not cover all structural variants attested across...... languages, semantic categories can be too wide, including too many structural variants. Furthermore, it appears that in some major typological studies semantic categories have been confused with formal categories. A possible solution is pointed out: typologists first need to make sure that the forms...

An Operational Semantics for Trust Policies

DEFF Research Database (Denmark)

Krukow, Karl

2006-01-01

In the trust-structure framework for trust management, principals specify their trusting relationships in terms of trust policies. In their paper on trust structures, Carbone et al. present a language for such policies, and provide a suitable denotational semantics. The semantics ensures that for......In the trust-structure framework for trust management, principals specify their trusting relationships in terms of trust policies. In their paper on trust structures, Carbone et al. present a language for such policies, and provide a suitable denotational semantics. The semantics ensures...... that for any collection of policies, there is always a unique global trust-state, compatible with all the policies, specifying everyone's degree of trust in everyone else. However, as the authors themselves point out, the language lacks an operational model: the global trust-state is a well......-defined mathematical object, but it is not clear how principals can actually compute it. This becomes even more apparent when one considers the intended application environment: vast numbers of autonomous principals, distributed and possibly mobile. We provide a compositional operational semantics for a language...

Unveiling Music Structure Via PLSA Similarity Fusion

DEFF Research Database (Denmark)

Arenas-García, Jerónimo; Meng, Anders; Petersen, Kaare Brandt

2007-01-01

Nowadays there is an increasing interest in developing methods for building music recommendation systems. In order to get a satisfactory performance from such a system, one needs to incorporate as much information about songs similarity as possible; however, how to do so is not obvious. In this p......Nowadays there is an increasing interest in developing methods for building music recommendation systems. In order to get a satisfactory performance from such a system, one needs to incorporate as much information about songs similarity as possible; however, how to do so is not obvious...... observed similarities can be satisfactorily explained using the latent semantics. Additionally, this approach significantly simplifies the song retrieval phase, leading to a more practical system implementation. The suitability of the PLSA model for representing music structure is studied in a simplified...

Handling of biological specimens for electron microscopy

International Nuclear Information System (INIS)

Bullock, G.

1987-01-01

There are many different aspects of specimen preparation procedure which need to be considered in order to achieve good results. Whether using the scanning or transmission microscope, the initial handling procedures are very similar and are selected for the information required. Handling procedures and techniques described are: structural preservation; immuno-and histo-chemistry; x-ray microanalysis and autoradiography; dehydration and embedding; mounting and coating specimens for scanning electron microscopy; and sectioning of resin embedded material. With attention to detail and careful choice of the best available technique, excellent results should be obtainable whatever the specimen. 6 refs

Semantic graphs and associative memories

Science.gov (United States)

Pomi, Andrés; Mizraji, Eduardo

2004-12-01

Graphs have been increasingly utilized in the characterization of complex networks from diverse origins, including different kinds of semantic networks. Human memories are associative and are known to support complex semantic nets; these nets are represented by graphs. However, it is not known how the brain can sustain these semantic graphs. The vision of cognitive brain activities, shown by modern functional imaging techniques, assigns renewed value to classical distributed associative memory models. Here we show that these neural network models, also known as correlation matrix memories, naturally support a graph representation of the stored semantic structure. We demonstrate that the adjacency matrix of this graph of associations is just the memory coded with the standard basis of the concept vector space, and that the spectrum of the graph is a code invariant of the memory. As long as the assumptions of the model remain valid this result provides a practical method to predict and modify the evolution of the cognitive dynamics. Also, it could provide us with a way to comprehend how individual brains that map the external reality, almost surely with different particular vector representations, are nevertheless able to communicate and share a common knowledge of the world. We finish presenting adaptive association graphs, an extension of the model that makes use of the tensor product, which provides a solution to the known problem of branching in semantic nets.

Memory for the perceptual and semantic attributes of information in pure amnesic and severe closed-head injured patients.

Science.gov (United States)

Carlesimo, Giovanni A; Bonanni, Rita; Caltagirone, Carlo

2003-05-01

This study investigated the hypothesis that brain damaged patients with memory disorder are poorer at remembering the semantic than the perceptual attributes of information. Eight patients with memory impairment of different etiology and 24 patients with chronic consequences of severe closed-head injury were compared to similarly sized age- and literacy-matched normal control groups on recognition tests for the physical aspect and the semantic identity of words and pictures lists. In order to avoid interpretative problems deriving from different absolute levels of performance, study conditions were manipulated across subjects to obtain comparable accuracy on the perceptual recognition tests in the memory disordered and control groups. The results of the Picture Recognition test were consistent with the hypothesis. Indeed, having more time for the stimulus encoding, the two memory disordered groups performed at the same level as the normal subjects on the perceptual test but significantly lower on the semantic test. Instead, on the Word Recognition test, following study condition manipulation, patients and controls performed similarly on both the perceptual and the semantic tests. These data only partially support the hypothesis of the study; rather they suggest that in memory disordered patients there is a reduction of the advantage, exhibited by normal controls, of retrieving pictures over words (picture superiority effect).

Semantic interpretation of search engine resultant

Science.gov (United States)

Nasution, M. K. M.

2018-01-01

In semantic, logical language can be interpreted in various forms, but the certainty of meaning is included in the uncertainty, which directly always influences the role of technology. One results of this uncertainty applies to search engines as user interfaces with information spaces such as the Web. Therefore, the behaviour of search engine results should be interpreted with certainty through semantic formulation as interpretation. Behaviour formulation shows there are various interpretations that can be done semantically either temporary, inclusion, or repeat.

Behavior Modification Through Covert Semantic Desensitization

Science.gov (United States)

Hekmat, Hamid; Vanian, Daniel

1971-01-01

Results support the hypothesized relationship between meaning and phobia. Semantic desensitization techniques based on counter conditioning of meaning were significantly effective in altering the semantic value of the word from unpleasantness to neutrality. (Author)

Semantic processing of EHR data for clinical research.

Science.gov (United States)

Sun, Hong; Depraetere, Kristof; De Roo, Jos; Mels, Giovanni; De Vloed, Boris; Twagirumukiza, Marc; Colaert, Dirk

2015-12-01

There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Semantic transparency affects morphological priming . . . eventually.

Science.gov (United States)

Heyer, Vera; Kornishova, Dana

2018-05-01

Semantic transparency has been in the focus of psycholinguistic research for decades, with the controversy about the time course of the application of morpho-semantic information during the processing of morphologically complex words not yet resolved. This study reports two masked priming studies with English - ness and Russian - ost' nominalisations, investigating how semantic transparency modulates native speakers' morphological priming effects at short and long stimulus onset asynchronies (SOAs). In both languages, we found increased morphological priming for nominalisations at the transparent end of the scale (e.g. paleness - pale) in comparison to items at the opaque end of the scale (e.g. business - busy) but only at longer prime durations. The present findings are in line with models that posit an initial phase of morpho-orthographic (semantically blind) decomposition.

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.

Extracting Semantic Information from Visual Data: A Survey

Directory of Open Access Journals (Sweden)

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.

Semantic web for integrated network analysis in biomedicine.

Science.gov (United States)

Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

2009-03-01

The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

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. �

Ontology Based Resolution of Semantic Conflicts in Information Integration

Institute of Scientific and Technical Information of China (English)

LU Han; LI Qing-zhong

2004-01-01

Semantic conflict is the conflict caused by using different ways in heterogeneous systems to express the same entity in reality.This prevents information integration from accomplishing semantic coherence.Since ontology helps to solve semantic problems, this area has become a hot topic in information integration.In this paper, we introduce semantic conflict into information integration of heterogeneous applications.We discuss the origins and categories of the conflict, and present an ontology-based schema mapping approach to eliminate semantic conflicts.

A logical correspondence between natural semantics and abstract machines

DEFF Research Database (Denmark)

Simmons, Robert J.; Zerny, Ian

2013-01-01

We present a logical correspondence between natural semantics and abstract machines. This correspondence enables the mechanical and fully-correct construction of an abstract machine from a natural semantics. Our logical correspondence mirrors the Reynolds functional correspondence, but we...... manipulate semantic specifications encoded in a logical framework instead of manipulating functional programs. Natural semantics and abstract machines are instances of substructural operational semantics. As a byproduct, using a substructural logical framework, we bring concurrent and stateful models...

Recognition during recall failure: Semantic feature matching as a mechanism for recognition of semantic cues when recall fails.

Science.gov (United States)

Cleary, Anne M; Ryals, Anthony J; Wagner, Samantha R

2016-01-01

Research suggests that a feature-matching process underlies cue familiarity-detection when cued recall with graphemic cues fails. When a test cue (e.g., potchbork) overlaps in graphemic features with multiple unrecalled studied items (e.g., patchwork, pitchfork, pocketbook, pullcork), higher cue familiarity ratings are given during recall failure of all of the targets than when the cue overlaps in graphemic features with only one studied target and that target fails to be recalled (e.g., patchwork). The present study used semantic feature production norms (McRae et al., Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005) to examine whether the same holds true when the cues are semantic in nature (e.g., jaguar is used to cue cheetah). Indeed, test cues (e.g., cedar) that overlapped in semantic features (e.g., a_tree, has_bark, etc.) with four unretrieved studied items (e.g., birch, oak, pine, willow) received higher cue familiarity ratings during recall failure than test cues that overlapped in semantic features with only two (also unretrieved) studied items (e.g., birch, oak), which in turn received higher familiarity ratings during recall failure than cues that did not overlap in semantic features with any studied items. These findings suggest that the feature-matching theory of recognition during recall failure can accommodate recognition of semantic cues during recall failure, providing a potential mechanism for conceptually-based forms of cue recognition during target retrieval failure. They also provide converging evidence for the existence of the semantic features envisaged in feature-based models of semantic knowledge representation and for those more concretely specified by the production norms of McRae et al. (Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005).

Safety of Information System on Emergence of Semantic Instability

Directory of Open Access Journals (Sweden)

Viacheslav Ernstovich Wolfengagen

2013-02-01

Full Text Available We study the question of the effect of semantic instability and a possible violation of the safe mode of the information system. A similar effect occurs in the construction of specialized information systems, such as the blogosphere and other dynamic online communities. In a more general formulation, we consider the problem of finding the individual on “information path” left by him that currently comes to the fore in information technology.

A Walk-based Semantically Enriched Tree Kernel Over Distributed Word Representations

DEFF Research Database (Denmark)

Srivastava, Shashank; Hovy, Dirk

2013-01-01

We propose a walk-based graph kernel that generalizes the notion of tree-kernels to continuous spaces. Our proposed approach subsumes a general framework for word-similarity, and in particular, provides a flexible way to incorporate distributed representations. Using vector representations......, such an approach captures both distributional semantic similarities among words as well as the structural relations between them (encoded as the structure of the parse tree). We show an efficient formulation to compute this kernel using simple matrix multiplication operations. We present our results on three...

Fuel handling machine and auxiliary systems for a fuel handling cell

International Nuclear Information System (INIS)

Suikki, M.

2013-10-01

This working report is an update for as well as a supplement to an earlier fuel handling machine design (Kukkola and Roennqvist 2006). A focus in the earlier design proposal was primarily on the selection of a mechanical structure and operating principle for the fuel handling machine. This report introduces not only a fuel handling machine design but also auxiliary fuel handling cell equipment and its operation. An objective of the design work was to verify the operating principles of and space allocations for fuel handling cell equipment. The fuel handling machine is a remote controlled apparatus capable of handling intensely radiating fuel assemblies in the fuel handling cell of an encapsulation plant. The fuel handling cell is air tight space radiation-shielded with massive concrete walls. The fuel handling machine is based on a bridge crane capable of traveling in the handling cell along wall tracks. The bridge crane has its carriage provided with a carousel type turntable having mounted thereon both fixed and telescopic masts. The fixed mast has a gripper movable on linear guides for the transfer of fuel assemblies. The telescopic mast has a manipulator arm capable of maneuvering equipment present in the fuel handling cell, as well as conducting necessary maintenance and cleaning operations or rectifying possible fault conditions. The auxiliary fuel handling cell systems consist of several subsystems. The subsystems include a service manipulator, a tool carrier for manipulators, a material hatch, assisting winches, a vacuum cleaner, as well as a hose reel. With the exception of the vacuum cleaner, the devices included in the fuel handling cell's auxiliary system are only used when the actual encapsulation process is not ongoing. The malfunctions of mechanisms or actuators responsible for the motion actions of a fuel handling machine preclude in a worst case scenario the bringing of the fuel handling cell and related systems to a condition appropriate for

Fuel handling machine and auxiliary systems for a fuel handling cell

Energy Technology Data Exchange (ETDEWEB)

Suikki, M. [Optimik Oy, Turku (Finland)

2013-10-15

This working report is an update for as well as a supplement to an earlier fuel handling machine design (Kukkola and Roennqvist 2006). A focus in the earlier design proposal was primarily on the selection of a mechanical structure and operating principle for the fuel handling machine. This report introduces not only a fuel handling machine design but also auxiliary fuel handling cell equipment and its operation. An objective of the design work was to verify the operating principles of and space allocations for fuel handling cell equipment. The fuel handling machine is a remote controlled apparatus capable of handling intensely radiating fuel assemblies in the fuel handling cell of an encapsulation plant. The fuel handling cell is air tight space radiation-shielded with massive concrete walls. The fuel handling machine is based on a bridge crane capable of traveling in the handling cell along wall tracks. The bridge crane has its carriage provided with a carousel type turntable having mounted thereon both fixed and telescopic masts. The fixed mast has a gripper movable on linear guides for the transfer of fuel assemblies. The telescopic mast has a manipulator arm capable of maneuvering equipment present in the fuel handling cell, as well as conducting necessary maintenance and cleaning operations or rectifying possible fault conditions. The auxiliary fuel handling cell systems consist of several subsystems. The subsystems include a service manipulator, a tool carrier for manipulators, a material hatch, assisting winches, a vacuum cleaner, as well as a hose reel. With the exception of the vacuum cleaner, the devices included in the fuel handling cell's auxiliary system are only used when the actual encapsulation process is not ongoing. The malfunctions of mechanisms or actuators responsible for the motion actions of a fuel handling machine preclude in a worst case scenario the bringing of the fuel handling cell and related systems to a condition appropriate for

“Pre-semantic” cognition revisited: Critical differences between semantic aphasia and semantic dementia

OpenAIRE

Jefferies, Elizabeth; Rogers, Timothy T.; Hopper, Samantha; Lambon Ralph, Matthew A.

2010-01-01

Patients with semantic dementia show a specific pattern of impairment on both verbal and non-verbal "pre-semantic" tasks, e.g., reading aloud, past tense generation, spelling to dictation, lexical decision, object decision, colour decision and delayed picture copying. All seven tasks are characterised by poorer performance for items that are atypical of the domain and "regularisation errors" (irregular/atypical items are produced as if they were domain-typical). The emergence of this pattern ...

Russian nominal semantics and morphology

DEFF Research Database (Denmark)

Nørgård-Sørensen, Jens

The principal idea behind this book is that lexis and grammar make up a single coherent structure. It is shown that the grammatical patterns of the different classes of Russian nominals are closely interconnected. They can be described as reflecting a limited set of semantic distinctions which ar...... or weaker, of Russian. Students will see a pattern in what is traditionally described as disparate subsystems, and linguists may be inspired to consider the theoretical points concerning language as a coherent system, determining usage.......The principal idea behind this book is that lexis and grammar make up a single coherent structure. It is shown that the grammatical patterns of the different classes of Russian nominals are closely interconnected. They can be described as reflecting a limited set of semantic distinctions which...... are also rooted in the lexical-semantic classification of Russian nouns. The presentation focuses on semantics, both lexical and grammatical, and not least the connection between these two levels of content. The principal theoretical impact is the insight that grammar and lexis should not be seen...

Semantic Web Services Challenge, Results from the First Year. Series: Semantic Web And Beyond, Volume 8.

Science.gov (United States)

Petrie, C.; Margaria, T.; Lausen, H.; Zaremba, M.

Explores trade-offs among existing approaches. Reveals strengths and weaknesses of proposed approaches, as well as which aspects of the problem are not yet covered. Introduces software engineering approach to evaluating semantic web services. Service-Oriented Computing is one of the most promising software engineering trends because of the potential to reduce the programming effort for future distributed industrial systems. However, only a small part of this potential rests on the standardization of tools offered by the web services stack. The larger part of this potential rests upon the development of sufficient semantics to automate service orchestration. Currently there are many different approaches to semantic web service descriptions and many frameworks built around them. A common understanding, evaluation scheme, and test bed to compare and classify these frameworks in terms of their capabilities and shortcomings, is necessary to make progress in developing the full potential of Service-Oriented Computing. The Semantic Web Services Challenge is an open source initiative that provides a public evaluation and certification of multiple frameworks on common industrially-relevant problem sets. This edited volume reports on the first results in developing common understanding of the various technologies intended to facilitate the automation of mediation, choreography and discovery for Web Services using semantic annotations. Semantic Web Services Challenge: Results from the First Year is designed for a professional audience composed of practitioners and researchers in industry. Professionals can use this book to evaluate SWS technology for their potential practical use. The book is also suitable for advanced-level students in computer science.

A Novel Mobile Video Community Discovery Scheme Using Ontology-Based Semantical Interest Capture

Directory of Open Access Journals (Sweden)

Ruiling Zhang

2016-01-01

Full Text Available Leveraging network virtualization technologies, the community-based video systems rely on the measurement of common interests to define and steady relationship between community members, which promotes video sharing performance and improves scalability community structure. In this paper, we propose a novel mobile Video Community discovery scheme using ontology-based semantical interest capture (VCOSI. An ontology-based semantical extension approach is proposed, which describes video content and measures video similarity according to video key word selection methods. In order to reduce the calculation load of video similarity, VCOSI designs a prefix-filtering-based estimation algorithm to decrease energy consumption of mobile nodes. VCOSI further proposes a member relationship estimate method to construct scalable and resilient node communities, which promotes video sharing capacity of video systems with the flexible and economic community maintenance. Extensive tests show how VCOSI obtains better performance results in comparison with other state-of-the-art solutions.

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...

Usage of semantic representations in recognition memory.

Science.gov (United States)

Nishiyama, Ryoji; Hirano, Tetsuji; Ukita, Jun

2017-11-01

Meanings of words facilitate false acceptance as well as correct rejection of lures in recognition memory tests, depending on the experimental context. This suggests that semantic representations are both directly and indirectly (i.e., mediated by perceptual representations) used in remembering. Studies using memory conjunction errors (MCEs) paradigms, in which the lures consist of component parts of studied words, have reported semantic facilitation of rejection of the lures. However, attending to components of the lures could potentially cause this. Therefore, we investigated whether semantic overlap of lures facilitates MCEs using Japanese Kanji words in which a whole-word image is more concerned in reading. Experiments demonstrated semantic facilitation of MCEs in a delayed recognition test (Experiment 1), and in immediate recognition tests in which participants were prevented from using phonological or orthographic representations (Experiment 2), and the salient effect on individuals with high semantic memory capacities (Experiment 3). Additionally, analysis of the receiver operating characteristic suggested that this effect is attributed to familiarity-based memory judgement and phantom recollection. These findings indicate that semantic representations can be directly used in remembering, even when perceptual representations of studied words are available.

Autobiographically significant concepts: more episodic than semantic in nature? An electrophysiological investigation of overlapping types of memory.

Science.gov (United States)

Renoult, Louis; Davidson, Patrick S R; Schmitz, Erika; Park, Lillian; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian

2015-01-01

A common assertion is that semantic memory emerges from episodic memory, shedding the distinctive contexts associated with episodes over time and/or repeated instances. Some semantic concepts, however, may retain their episodic origins or acquire episodic information during life experiences. The current study examined this hypothesis by investigating the ERP correlates of autobiographically significant (AS) concepts, that is, semantic concepts that are associated with vivid episodic memories. We inferred the contribution of semantic and episodic memory to AS concepts using the amplitudes of the N400 and late positive component, respectively. We compared famous names that easily brought to mind episodic memories (high AS names) against equally famous names that did not bring such recollections to mind (low AS names) on a semantic task (fame judgment) and an episodic task (recognition memory). Compared with low AS names, high AS names were associated with increased amplitude of the late positive component in both tasks. Moreover, in the recognition task, this effect of AS was highly correlated with recognition confidence. In contrast, the N400 component did not differentiate the high versus low AS names but, instead, was related to the amount of general knowledge participants had regarding each name. These results suggest that semantic concepts high in AS, such as famous names, have an episodic component and are associated with similar brain processes to those that are engaged by episodic memory. Studying AS concepts may provide unique insights into how episodic and semantic memory interact.

Semantic Context Detection Using Audio Event Fusion

Directory of Open Access Journals (Sweden)

Cheng Wen-Huang

2006-01-01

Full Text Available Semantic-level content analysis is a crucial issue in achieving efficient content retrieval and management. We propose a hierarchical approach that models audio events over a time series in order to accomplish semantic context detection. Two levels of modeling, audio event and semantic context modeling, are devised to bridge the gap between physical audio features and semantic concepts. In this work, hidden Markov models (HMMs are used to model four representative audio events, that is, gunshot, explosion, engine, and car braking, in action movies. At the semantic context level, generative (ergodic hidden Markov model and discriminative (support vector machine (SVM approaches are investigated to fuse the characteristics and correlations among audio events, which provide cues for detecting gunplay and car-chasing scenes. The experimental results demonstrate the effectiveness of the proposed approaches and provide a preliminary framework for information mining by using audio characteristics.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

AlShahrani, Mona; Hoehndorf, Robert

2018-01-01

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease's (or patient's) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

Alshahrani, Mona

2018-04-30

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease\\'s (or patient\\'s) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

Graph-based Operational Semantics of a Lazy Functional Languages

DEFF Research Database (Denmark)

Rose, Kristoffer Høgsbro

1992-01-01

Presents Graph Operational Semantics (GOS): a semantic specification formalism based on structural operational semantics and term graph rewriting. Demonstrates the method by specifying the dynamic ...

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.

The training for nuclear fuel handling at EDF

International Nuclear Information System (INIS)

Marion, J.P.

1999-01-01

The handling of fuel assemblies in a nuclear power plant presents 3 types of work: the taking delivery of fresh fuel, the refueling and the disposal of spent fuel. These operations are realized by teams made up of 3 handling operators and a supervisor. The refueling is made by 3*8-hour teams. These handling operations are important for the nuclear safety, a mishandling can damage the fuel cladding which is the first containment barrier, so a training center (CETIC) has been created. This center was founded in 1986 by EDF and Framatome, the purpose was to validate maintenance procedures, to test handling equipment and to train the teams which work on site. Various training programmes have been set up and a system of qualification degrees has been organized. The CETIC is fitted up with equipment that are full-sized mockups of real installations. Fuel assemblies don't react in a similar way to the different mechanical and neutronic stresses they undergo while they are in the core, they get deformed and the handling operations become more delicate. The mockup fuel assemblies are quite deformed to train the teams and prepare them to face any real situation. (A.C.)

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.

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.

The Influence of Semantic Neighbours on Visual Word Recognition

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Yates, Mark

2012-01-01

Although it is assumed that semantics is a critical component of visual word recognition, there is still much that we do not understand. One recent way of studying semantic processing has been in terms of semantic neighbourhood (SN) density, and this research has shown that semantic neighbours facilitate lexical decisions. However, it is not clear…

The role of the left anterior temporal lobe in semantic composition vs. semantic memory.

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Westerlund, Masha; Pylkkänen, Liina

2014-05-01

The left anterior temporal lobe (LATL) is robustly implicated in semantic processing by a growing body of literature. However, these results have emerged from two distinct bodies of work, addressing two different processing levels. On the one hand, the LATL has been characterized as a 'semantic hub׳ that binds features of concepts across a distributed network, based on results from semantic dementia and hemodynamic findings on the categorization of specific compared to basic exemplars. On the other, the LATL has been implicated in combinatorial operations in language, as shown by increased activity in this region associated with the processing of sentences and of basic phrases. The present work aimed to reconcile these two literatures by independently manipulating combination and concept specificity within a minimal MEG paradigm. Participants viewed simple nouns that denoted either low specificity (fish) or high specificity categories (trout) presented in either combinatorial (spotted fish/trout) or non-combinatorial contexts (xhsl fish/trout). By combining these paradigms from the two literatures, we directly compared the engagement of the LATL in semantic memory vs. semantic composition. Our results indicate that although noun specificity subtly modulates the LATL activity elicited by single nouns, it most robustly affects the size of the composition effect when these nouns are adjectivally modified, with low specificity nouns eliciting a much larger effect. We conclude that these findings are compatible with an account in which the specificity and composition effects arise from a shared mechanism of meaning specification. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Change management for semantic web services

CERN Document Server

Liu, Xumin; Bouguettaya, Athman

2011-01-01

Change Management for Semantic Web Services provides a thorough analysis of change management in the lifecycle of services for databases and workflows, including changes that occur at the individual service level or at the aggregate composed service level. This book describes taxonomy of changes that are expected in semantic service oriented environments. The process of change management consists of detecting, propagating, and reacting to changes. Change Management for Semantic Web Services is one of the first books that discuss the development of a theoretical foundation for managing changes

When the Wedding March becomes sad: Semantic memory impairment for music in the semantic variant of primary progressive aphasia.

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Macoir, Joël; Berubé-Lalancette, Sarah; Wilson, Maximiliano A; Laforce, Robert; Hudon, Carol; Gravel, Pierre; Potvin, Olivier; Duchesne, Simon; Monetta, Laura

2016-12-01

Music can induce particular emotions and activate semantic knowledge. In the semantic variant of primary progressive aphasia (svPPA), semantic memory is impaired as a result of anterior temporal lobe (ATL) atrophy. Semantics is responsible for the encoding and retrieval of factual knowledge about music, including associative and emotional attributes. In the present study, we report the performance of two individuals with svPPA in three experiments. NG with bilateral ATL atrophy and ND with atrophy largely restricted to the left ATL. Experiment 1 assessed the recognition of musical excerpts and both patients were unimpaired. Experiment 2 studied the emotions conveyed by music and only NG showed impaired performance. Experiment 3 tested the association of semantic concepts to musical excerpts and both patients were impaired. These results suggest that the right ATL seems essential for the recognition of emotions conveyed by music and that the left ATL is involved in binding music to semantics. They are in line with the notion that the ATLs are devoted to the binding of different modality-specific properties and suggest that they are also differentially involved in the processing of factual and emotional knowledge associated with music.

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration