Semantic Annotation of Unstructured Documents Using Concepts Similarity

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Fernando Pech

2017-01-01

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

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.

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.

Representation of Semantic Similarity in the Left Intraparietal Sulcus: Functional Magnetic Resonance Imaging Evidence

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Veerle Neyens

2017-08-01

Full Text Available According to a recent study, semantic similarity between concrete entities correlates with the similarity of activity patterns in left middle IPS during category naming. We examined the replicability of this effect under passive viewing conditions, the potential role of visuoperceptual similarity, where the effect is situated compared to regions that have been previously implicated in visuospatial attention, and how it compares to effects of object identity and location. Forty-six subjects participated. Subjects passively viewed pictures from two categories, musical instruments and vehicles. Semantic similarity between entities was estimated based on a concept-feature matrix obtained in more than 1,000 subjects. Visuoperceptual similarity was modeled based on the HMAX model, the AlexNet deep convolutional learning model, and thirdly, based on subjective visuoperceptual similarity ratings. Among the IPS regions examined, only left middle IPS showed a semantic similarity effect. The effect was significant in hIP1, hIP2, and hIP3. Visuoperceptual similarity did not correlate with similarity of activity patterns in left middle IPS. The semantic similarity effect in left middle IPS was significantly stronger than in the right middle IPS and also stronger than in the left or right posterior IPS. The semantic similarity effect was similar to that seen in the angular gyrus. Object identity effects were much more widespread across nearly all parietal areas examined. Location effects were relatively specific for posterior IPS and area 7 bilaterally. To conclude, the current findings replicate the semantic similarity effect in left middle IPS under passive viewing conditions, and demonstrate its anatomical specificity within a cytoarchitectonic reference frame. We propose that the semantic similarity effect in left middle IPS reflects the transient uploading of semantic representations in working memory.

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.

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.

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/.

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.

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.

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.

A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

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Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

2016-02-01

Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

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

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.

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.

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.

IntelliGO: a new vector-based semantic similarity measure including annotation origin

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Devignes Marie-Dominique

2010-12-01

Full Text Available Abstract Background The Gene Ontology (GO is a well known controlled vocabulary describing the biological process, molecular function and cellular component aspects of gene annotation. It has become a widely used knowledge source in bioinformatics for annotating genes and measuring their semantic similarity. These measures generally involve the GO graph structure, the information content of GO aspects, or a combination of both. However, only a few of the semantic similarity measures described so far can handle GO annotations differently according to their origin (i.e. their evidence codes. Results We present here a new semantic similarity measure called IntelliGO which integrates several complementary properties in a novel vector space model. The coefficients associated with each GO term that annotates a given gene or protein include its information content as well as a customized value for each type of GO evidence code. The generalized cosine similarity measure, used for calculating the dot product between two vectors, has been rigorously adapted to the context of the GO graph. The IntelliGO similarity measure is tested on two benchmark datasets consisting of KEGG pathways and Pfam domains grouped as clans, considering the GO biological process and molecular function terms, respectively, for a total of 683 yeast and human genes and involving more than 67,900 pair-wise comparisons. The ability of the IntelliGO similarity measure to express the biological cohesion of sets of genes compares favourably to four existing similarity measures. For inter-set comparison, it consistently discriminates between distinct sets of genes. Furthermore, the IntelliGO similarity measure allows the influence of weights assigned to evidence codes to be checked. Finally, the results obtained with a complementary reference technique give intermediate but correct correlation values with the sequence similarity, Pfam, and Enzyme classifications when compared to

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

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.

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

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

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.

Evolution of semantic systems

CERN Document Server

Küppers, Bernd-Olaf; Artmann, Stefan

2013-01-01

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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.

A Grammar-Based Semantic Similarity Algorithm for Natural Language Sentences

Science.gov (United States)

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.

Modulation of the semantic system by word imageability.

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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

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.

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

Safety of Information System on Emergence of Semantic Instability

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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.

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

Science.gov (United States)

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.

A Semantic Web-based System for Managing Clinical Archetypes.

Science.gov (United States)

Fernandez-Breis, Jesualdo Tomas; Menarguez-Tortosa, Marcos; Martinez-Costa, Catalina; Fernandez-Breis, Eneko; Herrero-Sempere, Jose; Moner, David; Sanchez, Jesus; Valencia-Garcia, Rafael; Robles, Montserrat

2008-01-01

Archetypes facilitate the sharing of clinical knowledge and therefore are a basic tool for achieving interoperability between healthcare information systems. In this paper, a Semantic Web System for Managing Archetypes is presented. This system allows for the semantic annotation of archetypes, as well for performing semantic searches. The current system is capable of working with both ISO13606 and OpenEHR archetypes.

Somatotopic Semantic Priming and Prediction in the Motor System

Science.gov (United States)

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

2016-01-01

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

Designing learning management system interoperability in semantic web

Science.gov (United States)

Anistyasari, Y.; Sarno, R.; Rochmawati, N.

2018-01-01

The extensive adoption of learning management system (LMS) has set the focus on the interoperability requirement. Interoperability is the ability of different computer systems, applications or services to communicate, share and exchange data, information, and knowledge in a precise, effective and consistent way. Semantic web technology and the use of ontologies are able to provide the required computational semantics and interoperability for the automation of tasks in LMS. The purpose of this study is to design learning management system interoperability in the semantic web which currently has not been investigated deeply. Moodle is utilized to design the interoperability. Several database tables of Moodle are enhanced and some features are added. The semantic web interoperability is provided by exploited ontology in content materials. The ontology is further utilized as a searching tool to match user’s queries and available courses. It is concluded that LMS interoperability in Semantic Web is possible to be performed.

Semantically optiMize the dAta seRvice operaTion (SMART) system for better data discovery and access

Science.gov (United States)

Yang, C.; Huang, T.; Armstrong, E. M.; Moroni, D. F.; Liu, K.; Gui, Z.

2013-12-01

Abstract: We present a Semantically optiMize the dAta seRvice operaTion (SMART) system for better data discovery and access across the NASA data systems, Global Earth Observation System of Systems (GEOSS) Clearinghouse and Data.gov to facilitate scientists to select Earth observation data that fit better their needs in four aspects: 1. Integrating and interfacing the SMART system to include the functionality of a) semantic reasoning based on Jena, an open source semantic reasoning engine, b) semantic similarity calculation, c) recommendation based on spatiotemporal, semantic, and user workflow patterns, and d) ranking results based on similarity between search terms and data ontology. 2. Collaborating with data user communities to a) capture science data ontology and record relevant ontology triple stores, b) analyze and mine user search and download patterns, c) integrate SMART into metadata-centric discovery system for community-wide usage and feedback, and d) customizing data discovery, search and access user interface to include the ranked results, recommendation components, and semantic based navigations. 3. Laying the groundwork to interface the SMART system with other data search and discovery systems as an open source data search and discovery solution. The SMART systems leverages NASA, GEO, FGDC data discovery, search and access for the Earth science community by enabling scientists to readily discover and access data appropriate to their endeavors, increasing the efficiency of data exploration and decreasing the time that scientists must spend on searching, downloading, and processing the datasets most applicable to their research. By incorporating the SMART system, it is a likely aim that the time being devoted to discovering the most applicable dataset will be substantially reduced, thereby reducing the number of user inquiries and likewise reducing the time and resources expended by a data center in addressing user inquiries. Keywords: EarthCube; ECHO

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...

Semantically Enhanced Recommender Systems

Science.gov (United States)

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

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

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 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

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.

Semantic technologies in a decision support system

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Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

2015-10-01

The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

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...

A Visual lexicon to Handle Semantic Similarity in Design precedents

DEFF Research Database (Denmark)

Restrepo-Giraldo, John Dairo

2007-01-01

The adequate use of existing knowledge, and not only the creation of completely new solutions, is also an important part of creative thinking. When conceiving a solution, designers oftentimes report having a vague image of the form that will embody the final solution to the design task at hand...... recognition techniques to index and retrieve visual information called Content Based Image Retrieval (CBIR). In this approach, the designer gives the computer tool an image and the computer searches for images that are similar to the example given. For this, the computer looks for geometrical features...... for visual information. The reason is that the algorithms available cannot recognize what the image contains (in semantic terms) but humans can, and with great facility. This ability was reflected in the searching process of the designers in our studies. It is very natural for them to expect living room...

Interpreting semantic clustering effects in free recall.

Science.gov (United States)

Manning, Jeremy R; Kahana, Michael J

2012-07-01

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

A development framework for semantically interoperable health information systems.

Science.gov (United States)

Lopez, Diego M; Blobel, Bernd G M E

2009-02-01

Semantic interoperability is a basic challenge to be met for new generations of distributed, communicating and co-operating health information systems (HIS) enabling shared care and e-Health. Analysis, design, implementation and maintenance of such systems and intrinsic architectures have to follow a unified development methodology. The Generic Component Model (GCM) is used as a framework for modeling any system to evaluate and harmonize state of the art architecture development approaches and standards for health information systems as well as to derive a coherent architecture development framework for sustainable, semantically interoperable HIS and their components. The proposed methodology is based on the Rational Unified Process (RUP), taking advantage of its flexibility to be configured for integrating other architectural approaches such as Service-Oriented Architecture (SOA), Model-Driven Architecture (MDA), ISO 10746, and HL7 Development Framework (HDF). Existing architectural approaches have been analyzed, compared and finally harmonized towards an architecture development framework for advanced health information systems. Starting with the requirements for semantic interoperability derived from paradigm changes for health information systems, and supported in formal software process engineering methods, an appropriate development framework for semantically interoperable HIS has been provided. The usability of the framework has been exemplified in a public health scenario.

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.

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...

Annotation and retrieval system of CAD models based on functional semantics

Science.gov (United States)

Wang, Zhansong; Tian, Ling; Duan, Wenrui

2014-11-01

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

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.

Transfer Effects of Semantic Networks on Expert Systems: Mindtools at Work.

Science.gov (United States)

Marra, Rose M.; Jonassen, David H.

2002-01-01

Discussion of computers as mindtools focuses on semantic networks and expert systems that help learners build a representation of what they know by designing their own knowledge bases. Describes a study of undergraduates that examined the effects of building semantic networks on the construction of expert systems. (Author/LRW)

Biomedical semantics in the Semantic Web.

Science.gov (United States)

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

2011-03-07

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

Documentary languages and knowledge organization systems in the context of the semantic web

Directory of Open Access Journals (Sweden)

Marilda Lopes Ginez de Lara

Full Text Available The aim of this study was to discuss the need for formal documentary languages as a condition for it to function in the Semantic Web. Based on a bibliographic review, Linked Open Data is presented as an initial condition for the operationalization of the Semantic Web, similar to the movement of Linked Open Vocabularies that aimed to promote interoperability among vocabularies. We highlight the Simple Knowledge Organization System format by analyzing its main characteristics and presenting the new standard ISO 25964-1/2:2011/2012 -Thesauri and interoperability with other vocabularies, that revises previous recommendations, adding requirements for the interoperability and mapping of vocabularies. We discuss conceptual problems in the formalization of vocabularies and the need to invest critically in its operationalization, suggesting alternatives to harness the mapping of vocabularies.

Enabling Semantic Queries Against the Spatial Database

Directory of Open Access Journals (Sweden)

PENG, X.

2012-02-01

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

Intelligent query processing for semantic mediation of information systems

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Saber Benharzallah

2011-11-01

Full Text Available We propose an intelligent and an efficient query processing approach for semantic mediation of information systems. We propose also a generic multi agent architecture that supports our approach. Our approach focuses on the exploitation of intelligent agents for query reformulation and the use of a new technology for the semantic representation. The algorithm is self-adapted to the changes of the environment, offers a wide aptitude and solves the various data conflicts in a dynamic way; it also reformulates the query using the schema mediation method for the discovered systems and the context mediation for the other systems.

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....

Semantator: annotating clinical narratives with semantic web ontologies.

Science.gov (United States)

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

2012-01-01

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

A novel architecture for information retrieval system based on semantic web

Science.gov (United States)

Zhang, Hui

2011-12-01

Nowadays, the web has enabled an explosive growth of information sharing (there are currently over 4 billion pages covering most areas of human endeavor) so that the web has faced a new challenge of information overhead. The challenge that is now before us is not only to help people locating relevant information precisely but also to access and aggregate a variety of information from different resources automatically. Current web document are in human-oriented formats and they are suitable for the presentation, but machines cannot understand the meaning of document. To address this issue, Berners-Lee proposed a concept of semantic web. With semantic web technology, web information can be understood and processed by machine. It provides new possibilities for automatic web information processing. A main problem of semantic web information retrieval is that when these is not enough knowledge to such information retrieval system, the system will return to a large of no sense result to uses due to a huge amount of information results. In this paper, we present the architecture of information based on semantic web. In addiction, our systems employ the inference Engine to check whether the query should pose to Keyword-based Search Engine or should pose to the Semantic Search Engine.

Semantic guidance of eye movements in real-world scenes.

Science.gov (United States)

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

2011-05-25

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

Metamodeling of Semantic Web Enabled Multiagent Systems

NARCIS (Netherlands)

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

2006-01-01

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

Semantic Coherence Facilitates Distributional Learning.

Science.gov (United States)

Ouyang, Long; Boroditsky, Lera; Frank, Michael C

2017-04-01

Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of association with other words (e.g., they both tend to occur with words like "deliver," "truck," "package"). In contrast to these computational results, artificial language learning experiments suggest that distributional statistics alone do not facilitate learning of linguistic categories. However, experiments in this paradigm expose participants to entirely novel words, whereas real language learners encounter input that contains some known words that are semantically organized. In three experiments, we show that (a) the presence of familiar semantic reference points facilitates distributional learning and (b) this effect crucially depends both on the presence of known words and the adherence of these known words to some semantic organization. Copyright © 2016 Cognitive Science Society, Inc.

Semantically Enriching the Search System of a Music Digital Library

Science.gov (United States)

de Juan, Paloma; Iglesias, Carlos

Traditional search systems are usually based on keywords, a very simple and convenient mechanism to express a need for information. This is the most popular way of searching the Web, although it is not always an easy task to accurately summarize a natural language query in a few keywords. Working with keywords means losing the context, which is the only thing that can help us deal with ambiguity. This is the biggest problem of keyword-based systems. Semantic Web technologies seem a perfect solution to this problem, since they make it possible to represent the semantics of a given domain. In this chapter, we present three projects, Harmos, Semusici and Cantiga, whose aim is to provide access to a music digital library. We will describe two search systems, a traditional one and a semantic one, developed in the context of these projects and compare them in terms of usability and effectiveness.

Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

Science.gov (United States)

Fox, P.

2012-04-01

The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

The semantic system is involved in mathematical problem solving.

Science.gov (United States)

Zhou, Xinlin; Li, Mengyi; Li, Leinian; Zhang, Yiyun; Cui, Jiaxin; Liu, Jie; Chen, Chuansheng

2018-02-01

Numerous studies have shown that the brain regions around bilateral intraparietal cortex are critical for number processing and arithmetical computation. However, the neural circuits for more advanced mathematics such as mathematical problem solving (with little routine arithmetical computation) remain unclear. Using functional magnetic resonance imaging (fMRI), this study (N = 24 undergraduate students) compared neural bases of mathematical problem solving (i.e., number series completion, mathematical word problem solving, and geometric problem solving) and arithmetical computation. Direct subject- and item-wise comparisons revealed that mathematical problem solving typically had greater activation than arithmetical computation in all 7 regions of the semantic system (which was based on a meta-analysis of 120 functional neuroimaging studies on semantic processing). Arithmetical computation typically had greater activation in the supplementary motor area and left precentral gyrus. The results suggest that the semantic system in the brain supports mathematical problem solving. Copyright © 2017 Elsevier Inc. All rights reserved.

Functional imaging of the semantic system: retrieval of sensory-experienced and verbally learned knowledge.

Science.gov (United States)

Noppeney, Uta; Price, Cathy J

2003-01-01

This paper considers how functional neuro-imaging can be used to investigate the organization of the semantic system and the limitations associated with this technique. The majority of the functional imaging studies of the semantic system have looked for divisions by varying stimulus category. These studies have led to divergent results and no clear anatomical hypotheses have emerged to account for the dissociations seen in behavioral studies. Only a few functional imaging studies have used task as a variable to differentiate the neural correlates of semantic features more directly. We extend these findings by presenting a new study that contrasts tasks that differentially weight sensory (color and taste) and verbally learned (origin) semantic features. Irrespective of the type of semantic feature retrieved, a common semantic system was activated as demonstrated in many previous studies. In addition, the retrieval of verbally learned, but not sensory-experienced, features enhanced activation in medial and lateral posterior parietal areas. We attribute these "verbally learned" effects to differences in retrieval strategy and conclude that evidence for segregation of semantic features at an anatomical level remains weak. We believe that functional imaging has the potential to increase our understanding of the neuronal infrastructure that sustains semantic processing but progress may require multiple experiments until a consistent explanatory framework emerges.

UML 2 Semantics and Applications

CERN Document Server

Lano, Kevin

2009-01-01

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

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

Directory of Open Access Journals (Sweden)

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.

Dynamic switching between semantic and episodic memory systems.

Science.gov (United States)

Kompus, Kristiina; Olsson, Carl-Johan; Larsson, Anne; Nyberg, Lars

2009-09-01

It has been suggested that episodic and semantic long-term memory systems interact during retrieval. Here we examined the flexibility of memory retrieval in an associative task taxing memories of different strength, assumed to differentially engage episodic and semantic memory. Healthy volunteers were pre-trained on a set of 36 face-name pairs over a 6-week period. Another set of 36 items was shown only once during the same time period. About 3 months after the training period all items were presented in a randomly intermixed order in an event-related fMRI study of face-name memory. Once presented items differentially activated anterior cingulate cortex and a right prefrontal region that previously have been associated with episodic retrieval mode. High-familiar items were associated with stronger activation of posterior cortices and a left frontal region. These findings fit a model of memory retrieval by which early processes determine, on a trial-by-trial basis, if the task can be solved by the default semantic system. If not, there is a dynamic shift to cognitive control processes that guide retrieval from episodic memory.

Elearning Systems Based on the Semantic Web

Directory of Open Access Journals (Sweden)

George Nicola Sammour

2006-06-01

Full Text Available ELearning has been identified as a strategic resource that can be utilized as an increasing variety of venues such as homes, workplaces, and traditional institutions of learning, education, and training. ELearning systems are becoming technologically sophisticated and complicated, with regard to training management or course management. Their use does not always match well with traditional modes of teaching and learning and much care needs to be taken when considering the use of ELearning in educational institutions. The use of semantic web in eLearning has been explored with regard to two application areas: 1 software that supports teachers in performing their tasks in flexible online educational settings, and 2 software that interpret the structure of distributed, self organized, and self-directed ELearning and web-based learning. The resulting system will be used by learners to perform the tasks they are asked to do more effectively in the context of gaining knowledge out of the material presented by teachers. These two application areas and related tasks require a semantic representation of educational entities and pedagogical material, specifically the structure and the techniques of the teaching-learning process. In most eLearning systems users are able to manage and reuse learning contents according to their needs without any access problems. However the quality of learning is not guaranteed. This paper emphasizes the integration of the semantic web technologies with Elearning systems, taking into consideration the standards and reusable Learning Objects LO. The advantage to improve the descriptions of content, context and structure of the learning materials and the benefits of providing access to the learning materials are also presented.

An Implementation of Semantic Web System for Information retrieval using J2EE Technologies.

OpenAIRE

B.Hemanth kumar,; Prof. M.Surendra Prasad Babu

2011-01-01

Accessing web resources (Information) is an essential facility provided by web applications to every body. Semantic web is one of the systems that provide a facility to access the resources through web service applications. Semantic web and web Services are new emerging web based technologies. An automatic information processing system can be developed by using semantic web and web services, each having its own contribution within the context of developing web-based information systems and ap...

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.

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

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

OpenAIRE

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

2017-01-01

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

Semantically Interoperable XML Data.

Science.gov (United States)

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

2013-09-01

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

Semantically Interoperable XML Data

Science.gov (United States)

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

2013-01-01

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

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...

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

Directory of Open Access Journals (Sweden)

Анна Александровна Смирнитская

2016-12-01

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

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.

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.

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

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.

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.

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.

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.

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.

Semantic Role Labeling

CERN Document Server

Palmer, Martha; Xue, Nianwen

2011-01-01

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

Development of intelligent semantic search system for rubber research data in Thailand

Science.gov (United States)

Kaewboonma, Nattapong; Panawong, Jirapong; Pianhanuruk, Ekkawit; Buranarach, Marut

2017-10-01

The rubber production of Thailand increased not only by strong demand from the world market, but was also stimulated strongly through the replanting program of the Thai Government from 1961 onwards. With the continuous growth of rubber research data volume on the Web, the search for information has become a challenging task. Ontologies are used to improve the accuracy of information retrieval from the web by incorporating a degree of semantic analysis during the search. In this context, we propose an intelligent semantic search system for rubber research data in Thailand. The research methods included 1) analyzing domain knowledge, 2) ontologies development, and 3) intelligent semantic search system development to curate research data in trusted digital repositories may be shared among the wider Thailand rubber research community.

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...

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

Geospatial Semantics and the Semantic Web

CERN Document Server

Ashish, Naveen

2011-01-01

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

An approach to define semantics for BPM systems interoperability

Science.gov (United States)

Rico, Mariela; Caliusco, María Laura; Chiotti, Omar; Rosa Galli, María

2015-04-01

This article proposes defining semantics for Business Process Management systems interoperability through the ontology of Electronic Business Documents (EBD) used to interchange the information required to perform cross-organizational processes. The semantic model generated allows aligning enterprise's business processes to support cross-organizational processes by matching the business ontology of each business partner with the EBD ontology. The result is a flexible software architecture that allows dynamically defining cross-organizational business processes by reusing the EBD ontology. For developing the semantic model, a method is presented, which is based on a strategy for discovering entity features whose interpretation depends on the context, and representing them for enriching the ontology. The proposed method complements ontology learning techniques that can not infer semantic features not represented in data sources. In order to improve the representation of these entity features, the method proposes using widely accepted ontologies, for representing time entities and relations, physical quantities, measurement units, official country names, and currencies and funds, among others. When the ontologies reuse is not possible, the method proposes identifying whether that feature is simple or complex, and defines a strategy to be followed. An empirical validation of the approach has been performed through a case study.

Accelerating cancer systems biology research through Semantic Web technology.

Science.gov (United States)

Wang, Zhihui; Sagotsky, Jonathan; Taylor, Thomas; Shironoshita, Patrick; Deisboeck, Thomas S

2013-01-01

Cancer systems biology is an interdisciplinary, rapidly expanding research field in which collaborations are a critical means to advance the field. Yet the prevalent database technologies often isolate data rather than making it easily accessible. The Semantic Web has the potential to help facilitate web-based collaborative cancer research by presenting data in a manner that is self-descriptive, human and machine readable, and easily sharable. We have created a semantically linked online Digital Model Repository (DMR) for storing, managing, executing, annotating, and sharing computational cancer models. Within the DMR, distributed, multidisciplinary, and inter-organizational teams can collaborate on projects, without forfeiting intellectual property. This is achieved by the introduction of a new stakeholder to the collaboration workflow, the institutional licensing officer, part of the Technology Transfer Office. Furthermore, the DMR has achieved silver level compatibility with the National Cancer Institute's caBIG, so users can interact with the DMR not only through a web browser but also through a semantically annotated and secure web service. We also discuss the technology behind the DMR leveraging the Semantic Web, ontologies, and grid computing to provide secure inter-institutional collaboration on cancer modeling projects, online grid-based execution of shared models, and the collaboration workflow protecting researchers' intellectual property. Copyright © 2012 Wiley Periodicals, Inc.

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.

[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.

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...

Grasping Ideas with the Motor System: Semantic Somatotopy in Idiom Comprehension

Science.gov (United States)

Hauk, Olaf; Pulvermüller, Friedemann

2009-01-01

Single words and sentences referring to bodily actions activate the motor cortex. However, this semantic grounding of concrete language does not address the critical question whether the sensory–motor system contributes to the processing of abstract meaning and thought. We examined functional magnetic resonance imaging activation to idioms and literal sentences including arm- and leg-related action words. A common left fronto-temporal network was engaged in sentence reading, with idioms yielding relatively stronger activity in (pre)frontal and middle temporal cortex. Crucially, somatotopic activation along the motor strip, in central and precentral cortex, was elicited by idiomatic and literal sentences, reflecting the body part reference of the words embedded in the sentences. Semantic somatotopy was most pronounced after sentence ending, thus reflecting sentence-level processing rather than that of single words. These results indicate that semantic representations grounded in the sensory–motor system play a role in the composition of sentence-level meaning, even in the case of idioms. PMID:19068489

Architecture for WSN Nodes Integration in Context Aware Systems Using Semantic Messages

Science.gov (United States)

Larizgoitia, Iker; Muguira, Leire; Vazquez, Juan Ignacio

Wireless sensor networks (WSN) are becoming extremely popular in the development of context aware systems. Traditionally WSN have been focused on capturing data, which was later analyzed and interpreted in a server with more computational power. In this kind of scenario the problem of representing the sensor information needs to be addressed. Every node in the network might have different sensors attached; therefore their correspondent packet structures will be different. The server has to be aware of the meaning of every single structure and data in order to be able to interpret them. Multiple sensors, multiple nodes, multiple packet structures (and not following a standard format) is neither scalable nor interoperable. Context aware systems have solved this problem with the use of semantic technologies. They provide a common framework to achieve a standard definition of any domain. Nevertheless, these representations are computationally expensive, so a WSN cannot afford them. The work presented in this paper tries to bridge the gap between the sensor information and its semantic representation, by defining a simple architecture that enables the definition of this information natively in a semantic way, achieving the integration of the semantic information in the network packets. This will have several benefits, the most important being the possibility of promoting every WSN node to a real semantic information source.

Improving integrative searching of systems chemical biology data using semantic annotation.

Science.gov (United States)

Chen, Bin; Ding, Ying; Wild, David J

2012-03-08

Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i) simplifies the process of building SPARQL queries, (ii) enables useful new kinds of queries on the data and (iii) makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Chem2Bio2OWL is available at http://chem2bio2rdf.org/owl. The document is available at http://chem2bio2owl.wikispaces.com.

Requirements for Semantic Educational Recommender Systems in Formal E-Learning Scenarios

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Jesus G. Boticario

2011-07-01

Full Text Available This paper analyzes how recommender systems can be applied to current e-learning systems to guide learners in personalized inclusive e-learning scenarios. Recommendations can be used to overcome current limitations of learning management systems in providing personalization and accessibility features. Recommenders can take advantage of standards-based solutions to provide inclusive support. To this end we have identified the need for developing semantic educational recommender systems, which are able to extend existing learning management systems with adaptive navigation support. In this paper we present three requirements to be considered in developing these semantic educational recommender systems, which are in line with the service-oriented approach of the third generation of learning management systems, namely: (i a recommendation model; (ii an open standards-based service-oriented architecture; and (iii a usable and accessible graphical user interface to deliver the recommendations.

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

Science.gov (United States)

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

2015-01-01

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

Methods and apparatus for capture and storage of semantic information with sub-files in a parallel computing system

Science.gov (United States)

Faibish, Sorin; Bent, John M; Tzelnic, Percy; Grider, Gary; Torres, Aaron

2015-02-03

Techniques are provided for storing files in a parallel computing system using sub-files with semantically meaningful boundaries. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a plurality of sub-files. The method comprises the steps of obtaining a user specification of semantic information related to the file; providing the semantic information as a data structure description to a data formatting library write function; and storing the semantic information related to the file with one or more of the sub-files in one or more storage nodes of the parallel computing system. The semantic information provides a description of data in the file. The sub-files can be replicated based on semantically meaningful boundaries.

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

Directory of Open Access Journals (Sweden)

Zhenyu Wu

2017-02-01

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

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

Science.gov (United States)

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

2017-02-20

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

Computer-aided System of Semantic Text Analysis of a Technical Specification

OpenAIRE

Zaboleeva-Zotova, Alla; Orlova, Yulia

2008-01-01

The given work is devoted to development of the computer-aided system of semantic text analysis of a technical specification. The purpose of this work is to increase efficiency of software engineering based on automation of semantic text analysis of a technical specification. In work it is offered and investigated the model of the analysis of the text of the technical project is submitted, the attribute grammar of a technical specification, intended for formalization of limited Ru...

Emergent Semantics Interoperability in Large-Scale Decentralized Information Systems

CERN Document Server

Cudré-Mauroux, Philippe

2008-01-01

Peer-to-peer systems are evolving with new information-system architectures, leading to the idea that the principles of decentralization and self-organization will offer new approaches in informatics, especially for systems that scale with the number of users or for which central authorities do not prevail. This book describes a new way of building global agreements (semantic interoperability) based only on decentralized, self-organizing interactions.

Exploitation of Semantic Building Model in Indoor Navigation Systems

Science.gov (United States)

Anjomshoaa, A.; Shayeganfar, F.; Tjoa, A. Min

2009-04-01

There are many types of indoor and outdoor navigation tools and methodologies available. A majority of these solutions are based on Global Positioning Systems (GPS) and instant video and image processing. These approaches are ideal for open world environments where very few information about the target location is available, but for large scale building environments such as hospitals, governmental offices, etc the end-user will need more detailed information about the surrounding context which is especially important in case of people with special needs. This paper presents a smart indoor navigation solution that is based on Semantic Web technologies and Building Information Model (BIM). The proposed solution is also aligned with Google Android's concepts to enlighten the realization of results. Keywords: IAI IFCXML, Building Information Model, Indoor Navigation, Semantic Web, Google Android, People with Special Needs 1 Introduction Built environment is a central factor in our daily life and a big portion of human life is spent inside buildings. Traditionally the buildings are documented using building maps and plans by utilization of IT tools such as computer-aided design (CAD) applications. Documenting the maps in an electronic way is already pervasive but CAD drawings do not suffice the requirements regarding effective building models that can be shared with other building-related applications such as indoor navigation systems. The navigation in built environment is not a new issue, however with the advances in emerging technologies like GPS, mobile and networked environments, and Semantic Web new solutions have been suggested to enrich the traditional building maps and convert them to smart information resources that can be reused in other applications and improve the interpretability with building inhabitants and building visitors. Other important issues that should be addressed in building navigation scenarios are location tagging and end-user communication

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

XSemantic: An Extension of LCA Based XML Semantic Search

Science.gov (United States)

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.

Improving integrative searching of systems chemical biology data using semantic annotation

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Chen Bin

2012-03-01

Full Text Available Abstract Background Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. Results We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i simplifies the process of building SPARQL queries, (ii enables useful new kinds of queries on the data and (iii makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Availability Chem2Bio2OWL is available at http://chem2bio2rdf.org/owl. The document is available at http://chem2bio2owl.wikispaces.com.

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

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

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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 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

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...

A chemical specialty semantic network for the Unified Medical Language System

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Morrey C

2012-05-01

Full Text Available Abstract Background Terms representing chemical concepts found the Unified Medical Language System (UMLS are used to derive an expanded semantic network with mutually exclusive semantic types. The UMLS Semantic Network (SN is composed of a collection of broad categories called semantic types (STs that are assigned to concepts. Within the UMLS’s coverage of the chemical domain, we find a great deal of concepts being assigned more than one ST. This leads to the situation where the extent of a given ST may contain concepts elaborating variegated semantics. A methodology for expanding the chemical subhierarchy of the SN into a finer-grained categorization of mutually exclusive types with semantically uniform extents is presented. We call this network a Chemical Specialty Semantic Network (CSSN. A CSSN is derived automatically from the existing chemical STs and their assignments. The methodology incorporates a threshold value governing the minimum size of a type’s extent needed for inclusion in the CSSN. Thus, different CSSNs can be created by choosing different threshold values based on varying requirements. Results A complete CSSN is derived using a threshold value of 300 and having 68 STs. It is used effectively to provide high-level categorizations for a random sample of compounds from the “Chemical Entities of Biological Interest” (ChEBI ontology. The effect on the size of the CSSN using various threshold parameter values between one and 500 is shown. Conclusions The methodology has several potential applications, including its use to derive a pre-coordinated guide for ST assignments to new UMLS chemical concepts, as a tool for auditing existing concepts, inter-terminology mapping, and to serve as an upper-level network for ChEBI.

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

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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.

An Elementary Semantics for Cardelli's System of Multiple Inheritance

NARCIS (Netherlands)

Fokkinga, M.M.

1987-01-01

In [Cardelli 84] Luca Cardelli gave a formal definition of a typed object-oriented language incorporating a sub-type relation used to describe multiple inheritance. Cardelli's fundamental result was a semantics for his system that enabled sub-typing to be modelled as straightforward set-inclusion.

Design and Implementation of e-Health System Based on Semantic Sensor Network Using IETF YANG

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Wenquan Jin

2018-02-01

Full Text Available Recently, healthcare services can be delivered effectively to patients anytime and anywhere using e-Health systems. e-Health systems are developed through Information and Communication Technologies (ICT that involve sensors, mobiles, and web-based applications for the delivery of healthcare services and information. Remote healthcare is an important purpose of the e-Health system. Usually, the eHealth system includes heterogeneous sensors from diverse manufacturers producing data in different formats. Device interoperability and data normalization is a challenging task that needs research attention. Several solutions are proposed in the literature based on manual interpretation through explicit programming. However, programmatically implementing the interpretation of the data sender and data receiver in the e-Health system for the data transmission is counterproductive as modification will be required for each new device added into the system. In this paper, an e-Health system with the Semantic Sensor Network (SSN is proposed to address the device interoperability issue. In the proposed system, we have used IETF YANG for modeling the semantic e-Health data to represent the information of e-Health sensors. This modeling scheme helps in provisioning semantic interoperability between devices and expressing the sensing data in a user-friendly manner. For this purpose, we have developed an ontology for e-Health data that supports different styles of data formats. The ontology is defined in YANG for provisioning semantic interpretation of sensing data in the system by constructing meta-models of e-Health sensors. The proposed approach assists in the auto-configuration of eHealth sensors and querying the sensor network with semantic interoperability support for the e-Health system.

Preserved cumulative semantic interference despite amnesia

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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.

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

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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

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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

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

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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.

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

SoyBase Simple Semantic Web Architecture and Protocol (SSWAP) Services

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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...

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...

Young children make their gestural communication systems more language-like: segmentation and linearization of semantic elements in motion events.

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Clay, Zanna; Pople, Sally; Hood, Bruce; Kita, Sotaro

2014-08-01

Research on Nicaraguan Sign Language, created by deaf children, has suggested that young children use gestures to segment the semantic elements of events and linearize them in ways similar to those used in signed and spoken languages. However, it is unclear whether this is due to children's learning processes or to a more general effect of iterative learning. We investigated whether typically developing children, without iterative learning, segment and linearize information. Gestures produced in the absence of speech to express a motion event were examined in 4-year-olds, 12-year-olds, and adults (all native English speakers). We compared the proportions of gestural expressions that segmented semantic elements into linear sequences and that encoded them simultaneously. Compared with adolescents and adults, children reshaped the holistic stimuli by segmenting and recombining their semantic features into linearized sequences. A control task on recognition memory ruled out the possibility that this was due to different event perception or memory. Young children spontaneously bring fundamental properties of language into their communication system. © The Author(s) 2014.

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.

Towards Development of Web-based Assessment System Based on Semantic Web Technology

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Hosam Farouk El-Sofany

2011-01-01

Full Text Available The assessment process in an educational system is an important and primordial part of its success to assure the correct way of knowledge transmission and to ensure that students are working correctly and succeed to acquire the needed knowledge. In this study, we aim to include Semantic Web technologies in the E-learning process, as new components. We use Semantic Web (SW to: 1 support the evaluation of open questions in e-learning courses, 2 support the creation of questions and exams automatically, 3 support the evaluation of exams created by the system. These components should allow for measuring academic performance, providing feedback mechanisms, and improving participative and collaborative ideas. Our goal is to use Semantic Web and Wireless technologies to design and implement the assessment system that allows the students, to take: web-based tutorials, quizzes, free exercises, and exams, to download: course reviews, previous exams and their model answers, to access the system through the Mobile and take quick quizzes and exercises. The system facilitates generation of automatic, balanced, and different exam sheets that contain different types of questions covering the entire curriculum, and display gradually from easiness to difficulty. The system provides the teachers and administrators with several services such as: store different types of questions, generate exams with specific criteria, and upload course assignments, exams, and reviews.

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.

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

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Mao Ye

2015-08-01

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

Principles of Linguistic Composition Below and Beyond the Clause—Elements of a semantic combinatorial system

DEFF Research Database (Denmark)

Bundgaard, Peer

2006-01-01

beyond the scope of the clause. To this end it exposes two major principles of semantic combination that are active through all levels of linguistic composition: viz. frame-schematic structure and narrative structure. These principles are considered as being components of a semantic combinatorial system...

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

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...

Semantic Linkage of Control Systems

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Rolf Andreas Rasenack

2006-01-01

Full Text Available Control systems are sets of interconnected hardware and software components which regulate the behaviour of processes. The software of modern control systems rises for some years by requirements regarding the flexibility and functionality. Thus the force of innovation grows on enterprises, since ever newer products in ever shorter time intervals must be made available. Associated hereby is the crucial shortening of the product life cycle, whose effects show up in reduced care of the software and the spares inventory. The aim, the concept presented here and developed in a modeling environment, is proved and ensures a minimum functionality of software components. Replacing software components of a control system verified for functionality by a framework at run-time and if necessary the software conditions will become adapted. Quintessential point of this implementation is the usage of an abstract syntax tree. Within its hierarchical structure meta information is attached to nodes and processed by the framework. With the development of the concept for semantic proving of software components the lifetime of software-based products is increased.

Combining semantic technologies with a content-based image retrieval system - Preliminary considerations

Science.gov (United States)

Chmiel, P.; Ganzha, M.; Jaworska, T.; Paprzycki, M.

2017-10-01

Nowadays, as a part of systematic growth of volume, and variety, of information that can be found on the Internet, we observe also dramatic increase in sizes of available image collections. There are many ways to help users browsing / selecting images of interest. One of popular approaches are Content-Based Image Retrieval (CBIR) systems, which allow users to search for images that match their interests, expressed in the form of images (query by example). However, we believe that image search and retrieval could take advantage of semantic technologies. We have decided to test this hypothesis. Specifically, on the basis of knowledge captured in the CBIR, we have developed a domain ontology of residential real estate (detached houses, in particular). This allows us to semantically represent each image (and its constitutive architectural elements) represented within the CBIR. The proposed ontology was extended to capture not only the elements resulting from image segmentation, but also "spatial relations" between them. As a result, a new approach to querying the image database (semantic querying) has materialized, thus extending capabilities of the developed system.

Design and development of semantic web-based system for computer science domain-specific information retrieval

Directory of Open Access Journals (Sweden)

Ritika Bansal

2016-09-01

Full Text Available In semantic web-based system, the concept of ontology is used to search results by contextual meaning of input query instead of keyword matching. From the research literature, there seems to be a need for a tool which can provide an easy interface for complex queries in natural language that can retrieve the domain-specific information from the ontology. This research paper proposes an IRSCSD system (Information retrieval system for computer science domain as a solution. This system offers advanced querying and browsing of structured data with search results automatically aggregated and rendered directly in a consistent user-interface, thus reducing the manual effort of users. So, the main objective of this research is design and development of semantic web-based system for integrating ontology towards domain-specific retrieval support. Methodology followed is a piecemeal research which involves the following stages. First Stage involves the designing of framework for semantic web-based system. Second stage builds the prototype for the framework using Protégé tool. Third Stage deals with the natural language query conversion into SPARQL query language using Python-based QUEPY framework. Fourth Stage involves firing of converted SPARQL queries to the ontology through Apache's Jena API to fetch the results. Lastly, evaluation of the prototype has been done in order to ensure its efficiency and usability. Thus, this research paper throws light on framework development for semantic web-based system that assists in efficient retrieval of domain-specific information, natural language query interpretation into semantic web language, creation of domain-specific ontology and its mapping with related ontology. This research paper also provides approaches and metrics for ontology evaluation on prototype ontology developed to study the performance based on accessibility of required domain-related information.

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

Automatic semantic role labelling using a memory-based learning system

Directory of Open Access Journals (Sweden)

Roser Morante

2008-05-01

Full Text Available In this paper we present a semantic role labelling system. The main component of the system is a memory-based classifier. The system has been trained with the Cast3LB-CoNLL-SemRol. The features encode information from dependency syntax. The results (F1 0.86 are comparable with state-of-the-art results (F1 around 0.86 from systems that use information from constituent syntax.

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

Science.gov (United States)

Harvey, Denise Y; Schnur, Tatiana T

2016-01-01

Naming pictures and matching words to pictures belonging to the same semantic category impairs performance relative to when stimuli come from different semantic categories (i.e., semantic interference). Despite similar semantic interference phenomena in both picture naming and word-picture matching tasks, the locus of interference has been attributed to different levels of the language system - lexical in naming and semantic in word-picture matching. Although both tasks involve access to shared semantic representations, the extent to which interference originates and/or has its locus at a shared level remains unclear, as these effects are often investigated in isolation. We manipulated semantic context in cyclical picture naming and word-picture matching tasks, and tested whether factors tapping semantic-level (generalization of interference to novel category items) and lexical-level processes (interactions with lexical frequency) affected the magnitude of interference, while also assessing whether interference occurs at a shared processing level(s) (transfer of interference across tasks). We found that semantic interference in naming was sensitive to both semantic- and lexical-level processes (i.e., larger interference for novel vs. old and low- vs. high-frequency stimuli), consistent with a semantically mediated lexical locus. Interference in word-picture matching exhibited stable interference for old and novel stimuli and did not interact with lexical frequency. Further, interference transferred from word-picture matching to naming. Together, these experiments provide evidence to suggest that semantic interference in both tasks originates at a shared processing stage (presumably at the semantic level), but that it exerts its effect at different loci when naming pictures vs. matching words to pictures.

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.

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

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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.

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

Science.gov (United States)

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

2009-09-23

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

Efficient computation of argumentation semantics

CERN Document Server

Liao, Beishui

2013-01-01

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

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

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.

WEATHER FORECAST DATA SEMANTIC ANALYSIS IN F-LOGIC

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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.

Integrating user profile in medical CBIR systems to answer perceptual similarity queries

Science.gov (United States)

Bugatti, Pedro H.; Kaster, Daniel S.; Ponciano-Silva, Marcelo; Traina, Agma J. M.; Traina, Caetano, Jr.

2011-03-01

Techniques for Content-Based Image Retrieval (CBIR) have been intensively explored due to the increase in the amount of captured images and the need of fast retrieval of them. The medical field is a specific example that generates a large flow of information, especially digital images employed for diagnosing. One issue that still remains unsolved deals with how to reach the perceptual similarity. That is, to achieve an effective retrieval, one must characterize and quantify the perceptual similarity regarding the specialist in the field. Therefore, the present paper was conceived to fill in this gap creating a consistent support to perform similarity queries over medical images, maintaining the semantics of a given query desired by the user. CBIR systems relying in relevance feedback techniques usually request the users to label relevant images. In this paper, we present a simple but highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The user profiles maintain the settings desired for each user, allowing tuning the similarity assessment, which encompasses dynamically changing the distance function employed through an interactive process. Experiments using computed tomography lung images show that the proposed approach is effective in capturing the users' perception.

NASA and The Semantic Web

Science.gov (United States)

Ashish, Naveen

2005-01-01

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

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.

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.

A Drone Remote Sensing for Virtual Reality Simulation System for Forest Fires: Semantic Neural Network Approach

Science.gov (United States)

Narasimha Rao, Gudikandhula; Jagadeeswara Rao, Peddada; Duvvuru, Rajesh

2016-09-01

Wild fires have significant impact on atmosphere and lives. The demand of predicting exact fire area in forest may help fire management team by using drone as a robot. These are flexible, inexpensive and elevated-motion remote sensing systems that use drones as platforms are important for substantial data gaps and supplementing the capabilities of manned aircraft and satellite remote sensing systems. In addition, powerful computational tools are essential for predicting certain burned area in the duration of a forest fire. The reason of this study is to built up a smart system based on semantic neural networking for the forecast of burned areas. The usage of virtual reality simulator is used to support the instruction process of fire fighters and all users for saving of surrounded wild lives by using a naive method Semantic Neural Network System (SNNS). Semantics are valuable initially to have a enhanced representation of the burned area prediction and better alteration of simulation situation to the users. In meticulous, consequences obtained with geometric semantic neural networking is extensively superior to other methods. This learning suggests that deeper investigation of neural networking in the field of forest fires prediction could be productive.

Auto-Generated Semantic Processing Services

Science.gov (United States)

Davis, Rodney; Hupf, Greg

2009-01-01

Auto-Generated Semantic Processing (AGSP) Services is a suite of software tools for automated generation of other computer programs, denoted cross-platform semantic adapters, that support interoperability of computer-based communication systems that utilize a variety of both new and legacy communication software running in a variety of operating- system/computer-hardware combinations. AGSP has numerous potential uses in military, space-exploration, and other government applications as well as in commercial telecommunications. The cross-platform semantic adapters take advantage of common features of computer- based communication systems to enforce semantics, messaging protocols, and standards of processing of streams of binary data to ensure integrity of data and consistency of meaning among interoperating systems. The auto-generation aspect of AGSP Services reduces development time and effort by emphasizing specification and minimizing implementation: In effect, the design, building, and debugging of software for effecting conversions among complex communication protocols, custom device mappings, and unique data-manipulation algorithms is replaced with metadata specifications that map to an abstract platform-independent communications model. AGSP Services is modular and has been shown to be easily integrable into new and legacy NASA flight and ground communication systems.

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.

The Universality of Semantic Prototypes in Spanish Lexical Availability

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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.

An Intelligent Knowledge Management System from a Semantic Perspective

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Vasile MAZILESCU

2008-01-01

Full Text Available Knowledge Management Systems (KMS are important tools by whichorganizations can better use information and, more importantly, manageknowledge. Unlike other strategies, knowledge management (KM is difficult todefine because it encompasses a range of concepts, management tasks,technologies, and organizational practices, all of which come under the umbrella ofthe information management. Semantic approaches allow easier and more efficienttraining, maintenance, and support knowledge. Current ICT markets are dominatedby relational databases and document-centric information technologies, proceduralalgorithmic programming paradigms, and stack architecture. A key driver of globaleconomic expansion in the coming decade is the build-out of broadbandtelecommunications and the deployment of intelligent services bundling. This paperintroduces the main characteristics of an Intelligent Knowledge ManagementSystem as a multiagent system used in a Learning Control Problem (IKMSLCP,from a semantic perspective. We describe an intelligent KM framework, allowingthe observer (a human agent to learn from experience. This framework makes thesystem dynamic (flexible and adaptable so it evolves, guaranteeing high levels ofstability when performing his domain problem P. To capture by the agent who learnthe control knowledge for solving a task-allocation problem, the control expertsystem uses at any time, an internal fuzzy knowledge model of the (businessprocess based on the last knowledge model.

Designing a federated multimedia information system on the semantic web

NARCIS (Netherlands)

Vdovják, R.; Barna, P.; Houben, G.J.P.M.; Eder, J.; Missikoff, M.

2003-01-01

A federated Web-based multimedia information system on one hand gathers its data from various Web sources, on the other hand offers the end-user a rich semantics describing its content and a user-friendly environment for expressing queries over its data. There are three essential ingredients to

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.

Developing Visualization Techniques for Semantics-based Information Networks

Science.gov (United States)

Keller, Richard M.; Hall, David R.

2003-01-01

Information systems incorporating complex network structured information spaces with a semantic underpinning - such as hypermedia networks, semantic networks, topic maps, and concept maps - are being deployed to solve some of NASA s critical information management problems. This paper describes some of the human interaction and navigation problems associated with complex semantic information spaces and describes a set of new visual interface approaches to address these problems. A key strategy is to leverage semantic knowledge represented within these information spaces to construct abstractions and views that will be meaningful to the human user. Human-computer interaction methodologies will guide the development and evaluation of these approaches, which will benefit deployed NASA systems and also apply to information systems based on the emerging Semantic Web.

Requirements for Semantic Educational Recommender Systems in Formal E-Learning Scenarios

OpenAIRE

Jesus G. Boticario; Olga C. Santos

2011-01-01

This paper analyzes how recommender systems can be applied to current e-learning systems to guide learners in personalized inclusive e-learning scenarios. Recommendations can be used to overcome current limitations of learning management systems in providing personalization and accessibility features. Recommenders can take advantage of standards-based solutions to provide inclusive support. To this end we have identified the need for developing semantic educational recommender systems, which ...

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.

Science.gov (United States)

Campoy, Guillermo; Baddeley, Alan

2008-05-01

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

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.

Latent semantic analysis.

Science.gov (United States)

Evangelopoulos, Nicholas E

2013-11-01

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

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 modeling and structural synthesis of onboard electronics protection means as open information system

Science.gov (United States)

Zhevnerchuk, D. V.; Surkova, A. S.; Lomakina, L. S.; Golubev, A. S.

2018-05-01

The article describes the component representation approach and semantic models of on-board electronics protection from ionizing radiation of various nature. Semantic models are constructed, the feature of which is the representation of electronic elements, protection modules, sources of impact in the form of blocks with interfaces. The rules of logical inference and algorithms for synthesizing the object properties of the semantic network, imitating the interface between the components of the protection system and the sources of radiation, are developed. The results of the algorithm are considered using the example of radiation-resistant microcircuits 1645RU5U, 1645RT2U and the calculation and experimental method for estimating the durability of on-board electronics.

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

Improving knowledge management systems with latent semantic analysis

International Nuclear Information System (INIS)

Sebok, A.; Plott, C.; LaVoie, N.

2006-01-01

Latent Semantic Analysis (LSA) offers a technique for improving lessons learned and knowledge management systems. These systems are expected to become more widely used in the nuclear industry, as experienced personnel leave and are replaced by younger, less-experienced workers. LSA is a machine learning technology that allows searching of text based on meaning rather than predefined keywords or categories. Users can enter and retrieve data using their own words, rather than relying on constrained language lists or navigating an artificially structured database. LSA-based tools can greatly enhance the usability and usefulness of knowledge management systems and thus provide a valuable tool to assist nuclear industry personnel in gathering and transferring worker expertise. (authors)

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 distance as a critical factor in icon design for in-car infotainment systems.

Science.gov (United States)

Silvennoinen, Johanna M; Kujala, Tuomo; Jokinen, Jussi P P

2017-11-01

In-car infotainment systems require icons that enable fluent cognitive information processing and safe interaction while driving. An important issue is how to find an optimised set of icons for different functions in terms of semantic distance. In an optimised icon set, every icon needs to be semantically as close as possible to the function it visually represents and semantically as far as possible from the other functions represented concurrently. In three experiments (N = 21 each), semantic distances of 19 icons to four menu functions were studied with preference rankings, verbal protocols, and the primed product comparisons method. The results show that the primed product comparisons method can be efficiently utilised for finding an optimised set of icons for time-critical applications out of a larger set of icons. The findings indicate the benefits of the novel methodological perspective into the icon design for safety-critical contexts in general. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

A semantic data dictionary method for database schema integration in CIESIN

Science.gov (United States)

Hinds, N.; Huang, Y.; Ravishankar, C.

1993-08-01

CIESIN (Consortium for International Earth Science Information Network) is funded by NASA to investigate the technology necessary to integrate and facilitate the interdisciplinary use of Global Change information. A clear of this mission includes providing a link between the various global change data sets, in particular the physical sciences and the human (social) sciences. The typical scientist using the CIESIN system will want to know how phenomena in an outside field affects his/her work. For example, a medical researcher might ask: how does air-quality effect emphysema? This and many similar questions will require sophisticated semantic data integration. The researcher who raised the question may be familiar with medical data sets containing emphysema occurrences. But this same investigator may know little, if anything, about the existance or location of air-quality data. It is easy to envision a system which would allow that investigator to locate and perform a ``join'' on two data sets, one containing emphysema cases and the other containing air-quality levels. No such system exists today. One major obstacle to providing such a system will be overcoming the heterogeneity which falls into two broad categories. ``Database system'' heterogeneity involves differences in data models and packages. ``Data semantic'' heterogeneity involves differences in terminology between disciplines which translates into data semantic issues, and varying levels of data refinement, from raw to summary. Our work investigates a global data dictionary mechanism to facilitate a merged data service. Specially, we propose using a semantic tree during schema definition to aid in locating and integrating heterogeneous databases.

Semantic-Based Concurrency Control for Object-Oriented Database Systems Supporting Real-Time Applications

National Research Council Canada - National Science Library

Lee, Juhnyoung; Son, Sang H

1994-01-01

.... This paper investigates major issues in designing semantic-based concurrency control for object-oriented database systems supporting real-time applications, and it describes approaches to solving...

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.

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)

Dynamic graph system for a semantic database

Science.gov (United States)

Mizell, David

2015-01-27

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

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...

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…

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.

Semantic representation of CDC-PHIN vocabulary using Simple Knowledge Organization System.

Science.gov (United States)

Zhu, Min; Mirhaji, Parsa

2008-11-06

PHIN Vocabulary Access and Distribution System (VADS) promotes the use of standards based vocabulary within CDC information systems. However, the current PHIN vocabulary representation hinders its wide adoption. Simple Knowledge Organization System (SKOS) is a W3C draft specification to support the formal representation of Knowledge Organization Systems (KOS) within the framework of the Semantic Web. We present a method of adopting SKOS to represent PHIN vocabulary in order to enable automated information sharing and integration.

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.

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

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.

Using Semantic Similarity In Automated Call Quality Evaluator For Call Centers

Directory of Open Access Journals (Sweden)

Ria A. Sagum

2015-08-01

Full Text Available Conversation between the agent and client are being evaluated manually by a quality assurance officer QA. This job is only one of the responsibilities being done by a QA and particularly eat ups a lot of time for them which lead to late evaluation results that may cause untimely response of the company to concerns raised by their clients. This research developed an application software that automates and evaluates the quality assurance in business process outsourcing companies or customer service management implementing sentence similarity. The developed system includes two modules speaker diarization which includes transcription and question and answer extraction and similarity checker which checks the similarity between the extracted answer and the answer of the call center agent to a question. The system was evaluated for Correctness of the extracted answers and accurateness of the evaluation for a particular call. Audio conversations were tested for the accuracy of the transcription module which has an accuracy of 27.96. The Precision Recall and F-measure of the extracted answer was tested as 78.03 96.26 and 86.19 respectively. The Accuracy of the system in evaluating a call is 70.

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.

Semantically based clinical TCM telemedicine systems

CERN Document Server

Wong, Allan K Y; Lin, Wilfred W K; Dillon, Tharam S; Chang, Elizabeth J

2015-01-01

Recent years have seen the development of two significant trends namely: the adoption of some Traditional Chinese Medicine Practices into mainstream Allopathic Western Medicine and the advent of the internet and broad band networks leading to an increased interest in the use of Telemedicine to deliver medical services. In this book, we see the convergence of these two trends leading to a semantically-based TCM Telemedicine system that utilizes an ontology to provide sharable knowledge in the TCM realm to achieve this. The underpinning research required the development of a three-layer architecture and an Ontology of the TCM knowledge. As TCM knowledge like all medical knowledge is not frozen in time it was important to develop an approach that would allow evolution of the Ontology when new evidence became available. In order for the system to be practically grounded it was important to work with an industry partner PuraPharm Group/HerbMiners Informatics Limited. This partnership was initiated through Professo...

Development of lexical-semantic language system: N400 priming effect for spoken words in 18- and 24-month old children.

Science.gov (United States)

Rämä, Pia; Sirri, Louah; Serres, Josette

2013-04-01

Our aim was to investigate whether developing language system, as measured by a priming task for spoken words, is organized by semantic categories. Event-related potentials (ERPs) were recorded during a priming task for spoken words in 18- and 24-month-old monolingual French learning children. Spoken word pairs were either semantically related (e.g., train-bike) or unrelated (e.g., chicken-bike). The results showed that the N400-like priming effect occurred in 24-month-olds over the right parietal-occipital recording sites. In 18-month-olds the effect was observed similarly to 24-month-olds only in those children with higher word production ability. The results suggest that words are categorically organized in the mental lexicon of children at the age of 2 years and even earlier in children with a high vocabulary. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

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

Science.gov (United States)

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.

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.

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

Directory of Open Access Journals (Sweden)

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.

A Collaborative Semantic Annotation System in Health: Towards a SOA Design for Knowledge Sharing in Ambient Intelligence

Directory of Open Access Journals (Sweden)

Gabriel Guerrero-Contreras

2017-01-01

Full Text Available People nowadays spend more and more time performing collaborative tasks at anywhere and anytime. Specifically, professionals want to collaborate with each other by using advanced technologies for sharing knowledge in order to improve/automatize business processes. Semantic web technologies offer multiple benefits such as data integration across sources and automation enablers. The conversion of the widespread Content Management Systems into its semantic equivalent is a relevant step, as this enables the benefits of the semantic web to be extended. The FLERSA annotation tool makes it possible. In particular, it converts the Joomla! CMS into its semantic equivalent. However, this tool is highly coupled with that specific Joomla! platform. Furthermore, ambient intelligent (AmI environments can be seen as a natural way to address complex interactions between users and their environment, which could be transparently supported through distributed information systems. However, to build distributed information systems for AmI environments it is necessary to make important design decisions and apply techniques at system/software architecture level. In this paper, a SOA-based design solution consisting of two services and an underlying middleware is combined with the FLERSA tool. It allows end-users to collaborate independently of technical details and specific context conditions and in a distributed, decentralized way.

Similarity Measure of Graphs

Directory of Open Access Journals (Sweden)

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.

Genome semantics, in silico multicellular systems and the Central Dogma.

Science.gov (United States)

Werner, Eric

2005-03-21

Genomes with their complexity and size present what appears to be an impossible challenge. Scientists speak in terms of decades or even centuries before we will understand how genomes and their hosts the cell and the city of cells that make up the multicellular context function. We believe that there will be surprisingly quick progress made in our understanding of genomes. The key is to stop taking the Central Dogma as the only direction in which genome research can scale the semantics of genomes. Instead a top-down approach coupled with a bottom-up approach may snare the unwieldy beast and make sense of genomes. The method we propose is to take in silico biology seriously. By developing in silico models of genomes cells and multicellular systems, we position ourselves to develop a theory of meaning for artificial genomes. Then using that develop a natural semantics of genomes.

Semantic-Web Technology: Applications at NASA

Science.gov (United States)

Ashish, Naveen

2004-01-01

We provide a description of work at the National Aeronautics and Space Administration (NASA) on building system based on semantic-web concepts and technologies. NASA has been one of the early adopters of semantic-web technologies for practical applications. Indeed there are several ongoing 0 endeavors on building semantics based systems for use in diverse NASA domains ranging from collaborative scientific activity to accident and mishap investigation to enterprise search to scientific information gathering and integration to aviation safety decision support We provide a brief overview of many applications and ongoing work with the goal of informing the external community of these NASA endeavors.

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

Science.gov (United States)

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…

The Interaction between Semantic Representation and Episodic Memory.

Science.gov (United States)

Fang, Jing; Rüther, Naima; Bellebaum, Christian; Wiskott, Laurenz; Cheng, Sen

2018-02-01

The experimental evidence on the interrelation between episodic memory and semantic memory is inconclusive. Are they independent systems, different aspects of a single system, or separate but strongly interacting systems? Here, we propose a computational role for the interaction between the semantic and episodic systems that might help resolve this debate. We hypothesize that episodic memories are represented as sequences of activation patterns. These patterns are the output of a semantic representational network that compresses the high-dimensional sensory input. We show quantitatively that the accuracy of episodic memory crucially depends on the quality of the semantic representation. We compare two types of semantic representations: appropriate representations, which means that the representation is used to store input sequences that are of the same type as those that it was trained on, and inappropriate representations, which means that stored inputs differ from the training data. Retrieval accuracy is higher for appropriate representations because the encoded sequences are less divergent than those encoded with inappropriate representations. Consistent with our model prediction, we found that human subjects remember some aspects of episodes significantly more accurately if they had previously been familiarized with the objects occurring in the episode, as compared to episodes involving unfamiliar objects. We thus conclude that the interaction with the semantic system plays an important role for episodic memory.

Extending a Hybrid Tag-Based Recommender System with Personalization

DEFF Research Database (Denmark)

Durao, Frederico; Dolog, Peter

2010-01-01

extension for a hybrid tag-based recommender system, which suggests similar Web pages based on the similarity of their tags. The semantic extension aims at discovering tag relations which are not considered in basic syntax similarity. With the goal of generating more semantically grounded recommendations......, the proposal extends a hybrid tag-based recommender system with a semantic factor, which looks for tag relations in different semantic sources. In order to evaluate the benefits acquired with the semantic extension, we have compared the new findings with results from a previous experiment involving 38 people......Tagging activity has been recently identified as a potential source of knowledge about personal interests, preferences, goals, and other attributes known from user models. Tags themselves can be therefore used for finding personalized recommendations of items. This paper proposes a semantic...

Quality model for semantic IS standards

NARCIS (Netherlands)

Folmer, Erwin Johan Albert

2011-01-01

Semantic IS (Information Systems) standards are essential for achieving interoperability between organizations. However a recent survey suggests that not the full benefits of standards are achieved, due to the quality issues. This paper presents a quality model for semantic IS standards, that should

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

Science.gov (United States)

Sui, Jie; Humphreys, Glyn W

2013-11-01

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

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.

Information retrieval system with ability of analogical inference using semantic network and function of fuzzification

Energy Technology Data Exchange (ETDEWEB)

Nakamura, K; Iwai, S

1982-01-01

In information retrieval system, it is necessary to grasp user's subject of interest in order to present appropriate documents to the user. In this paper, the authors propose a model of human ability of analogical inference based on association between key words and, using it, construct an information retrieval system in which the computer with the ability learns its user's subject of interest through question-answering with the user. In this system, the association between key words is represented by a semantic network, and a function of fuzzification of input information is introduced in the semantic network to implement the ability of analogical inference based on the association. Finally, the effect of analogical inference on the learning efficiency of the system is investigated. 5 references.

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

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

Science.gov (United States)

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.

Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning

Science.gov (United States)

Niemann, Katja; Wolpers, Martin

2015-01-01

In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new…

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

Science.gov (United States)

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.

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.

Enhancing acronym/abbreviation knowledge bases with semantic information.

Science.gov (United States)

Torii, Manabu; Liu, Hongfang

2007-10-11

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

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,

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’.

Convergence of Health Level Seven Version 2 Messages to Semantic Web Technologies for Software-Intensive Systems in Telemedicine Trauma Care.

Science.gov (United States)

Menezes, Pedro Monteiro; Cook, Timothy Wayne; Cavalini, Luciana Tricai

2016-01-01

To present the technical background and the development of a procedure that enriches the semantics of Health Level Seven version 2 (HL7v2) messages for software-intensive systems in telemedicine trauma care. This study followed a multilevel model-driven approach for the development of semantically interoperable health information systems. The Pre-Hospital Trauma Life Support (PHTLS) ABCDE protocol was adopted as the use case. A prototype application embedded the semantics into an HL7v2 message as an eXtensible Markup Language (XML) file, which was validated against an XML schema that defines constraints on a common reference model. This message was exchanged with a second prototype application, developed on the Mirth middleware, which was also used to parse and validate both the original and the hybrid messages. Both versions of the data instance (one pure XML, one embedded in the HL7v2 message) were equally validated and the RDF-based semantics recovered by the receiving side of the prototype from the shared XML schema. This study demonstrated the semantic enrichment of HL7v2 messages for intensive-software telemedicine systems for trauma care, by validating components of extracts generated in various computing environments. The adoption of the method proposed in this study ensures the compliance of the HL7v2 standard in Semantic Web technologies.

Principal semantic components of language and the measurement of meaning.

Science.gov (United States)

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

2010-06-11

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

Principal semantic components of language and the measurement of meaning.

Directory of Open Access Journals (Sweden)

Alexei V Samsonovich

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

Acoustic and semantic interference effects in words and pictures.

Science.gov (United States)

Dhawan, M; Pellegrino, J W

1977-05-01

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

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.

Concurrent semantics for structured design methods

OpenAIRE

Nixon, Patrick

1996-01-01

Also in Jelly, I., Gordon, I., & Groll, P. Software Engineering for Parallel and Distributed Systems. London: Chapman Hall. Design methods can be ambiguous due to di#11;erent interpretations of symbols or concepts. This paper presents a formal semantics for the Ward/Mellor Structured Analysis Method for Real Time systems. These semantics ensures that an unambiguous meaning can be attributed to a particular design. Speci#12;cally, it ensures that concurrent and real-time propert...

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

Science.gov (United States)

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

2015-12-01

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

Semantic Enhancement for Enterprise Data Management

Science.gov (United States)

Ma, Li; Sun, Xingzhi; Cao, Feng; Wang, Chen; Wang, Xiaoyuan; Kanellos, Nick; Wolfson, Dan; Pan, Yue

Taking customer data as an example, the paper presents an approach to enhance the management of enterprise data by using Semantic Web technologies. Customer data is the most important kind of core business entity a company uses repeatedly across many business processes and systems, and customer data management (CDM) is becoming critical for enterprises because it keeps a single, complete and accurate record of customers across the enterprise. Existing CDM systems focus on integrating customer data from all customer-facing channels and front and back office systems through multiple interfaces, as well as publishing customer data to different applications. To make the effective use of the CDM system, this paper investigates semantic query and analysis over the integrated and centralized customer data, enabling automatic classification and relationship discovery. We have implemented these features over IBM Websphere Customer Center, and shown the prototype to our clients. We believe that our study and experiences are valuable for both Semantic Web community and data management community.

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...

Generative Semantics.

Science.gov (United States)

King, Margaret

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

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

Directory of Open Access Journals (Sweden)

Petter Kallioinen

2016-08-01

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

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.

Exploring DBpedia and Wikipedia for Portuguese Semantic Relationship Extraction

Directory of Open Access Journals (Sweden)

David Soares Batista

2013-07-01

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

Constraint-Based Abstract Semantics for Temporal Logic

DEFF Research Database (Denmark)

Banda, Gourinath; Gallagher, John Patrick

2010-01-01

Abstract interpretation provides a practical approach to verifying properties of infinite-state systems. We apply the framework of abstract interpretation to derive an abstract semantic function for the modal mu-calculus, which is the basis for abstract model checking. The abstract semantic funct...

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

An Algebraic Specification of the Semantic Web

OpenAIRE

Ksystra, Katerina; Triantafyllou, Nikolaos; Stefaneas, Petros; Frangos, Panayiotis

2011-01-01

We present a formal specification of the Semantic Web, as an extension of the World Wide Web using the well known algebraic specification language CafeOBJ. Our approach allows the description of the key elements of the Semantic Web technologies, in order to give a better understanding of the system, without getting involved with their implementation details that might not yet be standardized. This specification is part of our work in progress concerning the modeling the Social Semantic Web.

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.

Can social semantic web techniques foster collaborative curriculum mapping in medicine?

Science.gov (United States)

Spreckelsen, Cord; Finsterer, Sonja; Cremer, Jan; Schenkat, Hennig

2013-08-15

formative usability study yielded positive results (median rating of 2 ("good") in all 7 general usability items) and produced valuable qualitative feedback, especially concerning navigation and comprehensibility. Although not asked to, the participants (n=5) detected critical aspects of the curriculum (similar learning objectives addressed repeatedly and missing objectives), thus proving the system's ability to support curriculum revision. The SMW-based approach enabled an agile implementation of computer-supported knowledge management. The approach, based on standard Social Semantic Web formats and technology, represents a feasible and effectively applicable compromise between answering to the individual requirements of curriculum management at a particular medical school and using proprietary systems.

SCALEUS: Semantic Web Services Integration for Biomedical Applications.

Science.gov (United States)

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

2017-04-01

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

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

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

Directory of Open Access Journals (Sweden)

Anwar A. H. Al-Athwary

2016-07-01

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

Semantic Interoperability in Heterogeneous IoT Infrastructure for Healthcare

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Sohail Jabbar

2017-01-01

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

The MMI Semantic Framework: Rosetta Stones for Earth Sciences

Science.gov (United States)

Rueda, C.; Bermudez, L. E.; Graybeal, J.; Alexander, P.

2009-12-01

Semantic interoperability—the exchange of meaning among computer systems—is needed to successfully share data in Ocean Science and across all Earth sciences. The best approach toward semantic interoperability requires a designed framework, and operationally tested tools and infrastructure within that framework. Currently available technologies make a scientific semantic framework feasible, but its development requires sustainable architectural vision and development processes. This presentation outlines the MMI Semantic Framework, including recent progress on it and its client applications. The MMI Semantic Framework consists of tools, infrastructure, and operational and community procedures and best practices, to meet short-term and long-term semantic interoperability goals. The design and prioritization of the semantic framework capabilities are based on real-world scenarios in Earth observation systems. We describe some key uses cases, as well as the associated requirements for building the overall infrastructure, which is realized through the MMI Ontology Registry and Repository. This system includes support for community creation and sharing of semantic content, ontology registration, version management, and seamless integration of user-friendly tools and application programming interfaces. The presentation describes the architectural components for semantic mediation, registry and repository for vocabularies, ontology, and term mappings. We show how the technologies and approaches in the framework can address community needs for managing and exchanging semantic information. We will demonstrate how different types of users and client applications exploit the tools and services for data aggregation, visualization, archiving, and integration. Specific examples from OOSTethys (http://www.oostethys.org) and the Ocean Observatories Initiative Cyberinfrastructure (http://www.oceanobservatories.org) will be cited. Finally, we show how semantic augmentation of web

Effects of Data Passing Semantics and Operating System Structure on Network I/O Performance

National Research Council Canada - National Science Library

Brustoloni, Jose

1997-01-01

.... Researchers have often proposed changing the semantics of I/O data passing, so as to make copying unnecessary, or the structure of the operating system, so as to reduce or eliminate data and control passing...

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

Science.gov (United States)

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.

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.

Semantic Web and Model-Driven Engineering

CERN Document Server

Parreiras, Fernando S

2012-01-01

The next enterprise computing era will rely on the synergy between both technologies: semantic web and model-driven software development (MDSD). The semantic web organizes system knowledge in conceptual domains according to its meaning. It addresses various enterprise computing needs by identifying, abstracting and rationalizing commonalities, and checking for inconsistencies across system specifications. On the other side, model-driven software development is closing the gap among business requirements, designs and executables by using domain-specific languages with custom-built syntax and se

The Husserlian Lebenswelt and the Semantic Conception of Theories

Directory of Open Access Journals (Sweden)

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

Directory of Open Access Journals (Sweden)

Alice F Jackson

2014-05-01

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

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 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.

A Collaborative System Software Solution for Modeling Business Flows Based on Automated Semantic Web Service Composition

Directory of Open Access Journals (Sweden)

Ion SMEUREANU

2009-01-01

Full Text Available Nowadays, business interoperability is one of the key factors for assuring competitive advantage for the participant business partners. In order to implement business cooperation, scalable, distributed and portable collaborative systems have to be implemented. This article presents some of the mostly used technologies in this field. Furthermore, it presents a software application architecture based on Business Process Modeling Notation standard and automated semantic web service coupling for modeling business flow in a collaborative manner. The main business processes will be represented in a single, hierarchic flow diagram. Each element of the diagram will represent calls to semantic web services. The business logic (the business rules and constraints will be structured with the help of OWL (Ontology Web Language. Moreover, OWL will also be used to create the semantic web service specifications.

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.…

Are there mental lexicons? The role of semantics in lexical decision.

Science.gov (United States)

Dilkina, Katia; McClelland, James L; Plaut, David C

2010-12-13

What is the underlying representation of lexical knowledge? How do we know whether a given string of letters is a word, whereas another string of letters is not? There are two competing models of lexical processing in the literature. The first proposes that we rely on mental lexicons. The second claims there are no mental lexicons; we identify certain items as words based on semantic knowledge. Thus, the former approach - the multiple-systems view - posits that lexical and semantic processing are subserved by separate systems, whereas the latter approach - the single-system view - holds that the two are interdependent. Semantic dementia patients, who have a cross-modal semantic impairment, show an accompanying and related lexical deficit. These findings support the single-system approach. However, a report of an SD patient whose impairment on lexical decision was not related to his semantic deficits in item-specific ways has presented a challenge to this view. If the two types of processing rely on a common system, then shouldn't damage impair the same items on all tasks? We present a single-system model of lexical and semantic processing, where there are no lexicons, and performance on lexical decision involves the activation of semantic representations. We show how, when these representations are damaged, accuracy on semantic and lexical tasks falls off together, but not necessarily on the same set of items. These findings are congruent with the patient data. We provide an explicit explanation of this pattern of results in our model, by defining and measuring the effects of two orthogonal factors - spelling consistency and concept consistency. Copyright © 2010 Elsevier B.V. All rights reserved.

Using semantic technologies and the OSU ontology for modelling context and activities in multi-sensory surveillance systems

Science.gov (United States)

Gómez A, Héctor F.; Martínez-Tomás, Rafael; Arias Tapia, Susana A.; Rincón Zamorano, Mariano

2014-04-01

Automatic systems that monitor human behaviour for detecting security problems are a challenge today. Previously, our group defined the Horus framework, which is a modular architecture for the integration of multi-sensor monitoring stages. In this work, structure and technologies required for high-level semantic stages of Horus are proposed, and the associated methodological principles established with the aim of recognising specific behaviours and situations. Our methodology distinguishes three semantic levels of events: low level (compromised with sensors), medium level (compromised with context), and high level (target behaviours). The ontology for surveillance and ubiquitous computing has been used to integrate ontologies from specific domains and together with semantic technologies have facilitated the modelling and implementation of scenes and situations by reusing components. A home context and a supermarket context were modelled following this approach, where three suspicious activities were monitored via different virtual sensors. The experiments demonstrate that our proposals facilitate the rapid prototyping of this kind of systems.

Semantic Technologies for Nuclear Knowledge Modelling and Applications

International Nuclear Information System (INIS)

Beraha, D.; Gladyshev, M.

2016-01-01

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

A semantics-based method for clustering of Chinese web search results

Science.gov (United States)

Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong

2014-01-01

Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.

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

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.

Development of similarity theory for control systems

Science.gov (United States)

Myshlyaev, L. P.; Evtushenko, V. F.; Ivushkin, K. A.; Makarov, G. V.

2018-05-01

The area of effective application of the traditional similarity theory and the need necessity of its development for systems are discussed. The main statements underlying the similarity theory of control systems are given. The conditions for the similarity of control systems and the need for similarity control control are formulated. Methods and algorithms for estimating and similarity control of control systems and the results of research of control systems based on their similarity are presented. The similarity control of systems includes the current evaluation of the degree of similarity of control systems and the development of actions controlling similarity, and the corresponding targeted change in the state of any element of control systems.

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 Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review

OpenAIRE

Zeng, Marcia Lei; Mayr, Philipp

2018-01-01

Since the Simple Knowledge Organization System (SKOS) specification and its SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a significant number of conventional knowledge organization systems (KOS) (including thesauri, classification schemes, name authorities, and lists of codes and terms, produced before the arrival of the ontology-wave) have made their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS" as an umbrella term to refer to all of...

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

Semantically-Rigorous Systems Engineering Modeling Using Sysml and OWL

Science.gov (United States)

Jenkins, J. Steven; Rouquette, Nicolas F.

2012-01-01

The Systems Modeling Language (SysML) has found wide acceptance as a standard graphical notation for the domain of systems engineering. SysML subsets and extends the Unified Modeling Language (UML) to define conventions for expressing structural, behavioral, and analytical elements, and relationships among them. SysML-enabled modeling tools are available from multiple providers, and have been used for diverse projects in military aerospace, scientific exploration, and civil engineering. The Web Ontology Language (OWL) has found wide acceptance as a standard notation for knowledge representation. OWL-enabled modeling tools are available from multiple providers, as well as auxiliary assets such as reasoners and application programming interface libraries, etc. OWL has been applied to diverse projects in a wide array of fields. While the emphasis in SysML is on notation, SysML inherits (from UML) a semantic foundation that provides for limited reasoning and analysis. UML's partial formalization (FUML), however, does not cover the full semantics of SysML, which is a substantial impediment to developing high confidence in the soundness of any conclusions drawn therefrom. OWL, by contrast, was developed from the beginning on formal logical principles, and consequently provides strong support for verification of consistency and satisfiability, extraction of entailments, conjunctive query answering, etc. This emphasis on formal logic is counterbalanced by the absence of any graphical notation conventions in the OWL standards. Consequently, OWL has had only limited adoption in systems engineering. The complementary strengths and weaknesses of SysML and OWL motivate an interest in combining them in such a way that we can benefit from the attractive graphical notation of SysML and the formal reasoning of OWL. This paper describes an approach to achieving that combination.

F-OWL: An Inference Engine for Semantic Web

Science.gov (United States)

Zou, Youyong; Finin, Tim; Chen, Harry

2004-01-01

Understanding and using the data and knowledge encoded in semantic web documents requires an inference engine. F-OWL is an inference engine for the semantic web language OWL language based on F-logic, an approach to defining frame-based systems in logic. F-OWL is implemented using XSB and Flora-2 and takes full advantage of their features. We describe how F-OWL computes ontology entailment and compare it with other description logic based approaches. We also describe TAGA, a trading agent environment that we have used as a test bed for F-OWL and to explore how multiagent systems can use semantic web concepts and technology.

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.

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*

Directory of Open Access Journals (Sweden)

Ronald Moe

2011-10-01

Full Text Available

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

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

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

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...

Age-related vulnerability in the neural systems supporting semantic processing

Directory of Open Access Journals (Sweden)

Jonathan E Peelle

2013-09-01

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

Towards the multilingual semantic web principles, methods and applications

CERN Document Server

Buitelaar, Paul

2014-01-01

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

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.

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.

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

Science.gov (United States)

Wiese, Holger; Schweinberger, Stefan R

2015-01-01

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

Facilitating Semantic Interoperability Among Ocean Data Systems: ODIP-R2R Student Outcomes

Science.gov (United States)

Stocks, K. I.; Chen, Y.; Shepherd, A.; Chandler, C. L.; Dockery, N.; Elya, J. L.; Smith, S. R.; Ferreira, R.; Fu, L.; Arko, R. A.

2014-12-01

With informatics providing an increasingly important set of tools for geoscientists, it is critical to train the next generation of scientists in information and data techniques. The NSF-supported Rolling Deck to Repository (R2R) Program works with the academic fleet community to routinely document, assess, and preserve the underway sensor data from U.S. research vessels. The Ocean Data Interoperability Platform (ODIP) is an EU-US-Australian collaboration fostering interoperability among regional e-infrastructures through workshops and joint prototype development. The need to align terminology between systems is a common challenge across all of the ODIP prototypes. Five R2R students were supported to address aspects of semantic interoperability within ODIP. Developing a vocabulary matching service that links terms from different vocabularies with similar concept. The service implements Google Refine reconciliation service interface such that users can leverage Google Refine application as a friendly user interface while linking different vocabulary terms. Developing Resource Description Framework (RDF) resources that map Shipboard Automated Meteorological Oceanographic System (SAMOS) vocabularies to internationally served vocabularies. Each SAMOS vocabulary term (data parameter and quality control flag) will be described as an RDF resource page. These RDF resources allow for enhanced discoverability and retrieval of SAMOS data by enabling data searches based on parameter. Improving data retrieval and interoperability by exposing data and mapped vocabularies using Semantic Web technologies. We have collaborated with ODIP participating organizations in order to build a generalized data model that will be used to populate a SPARQL endpoint in order to provide expressive querying over our data files. Mapping local and regional vocabularies used by R2R to those used by ODIP partners. This work is described more fully in a companion poster. Making published Linked Data

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.

Science.gov (United States)

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.

Semantic Web Technologies to Reconcile Privacy and Context Awareness

National Research Council Canada - National Science Library

Gandon, Fabien L; Sadeh, Norman M

2003-01-01

...; they may use different calendar systems, etc. In this article, we describe work on a Semantic e-Wallet aimed at supporting automated identification and access of personal resources, each represented as a Semantic Web Service...

a framework for semantic driven electronic examination system

African Journals Online (AJOL)

HOD

The framework is implemented using Java programming language ... Ontolog have been suggested as a cornerstone to solve ... is the background of study and problem statement, ... requires concept of ontology or semantic knowledge.

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.

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

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

Science.gov (United States)

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

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

Science.gov (United States)

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

2007-01-01

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

Definition of Business Rules Using Business Vocabulary and Semantics

Directory of Open Access Journals (Sweden)

Roman Hypský

2017-12-01

Full Text Available This paper discusses the definition of business rules using business vocabulary and semantics. At the beginning business rules, business vocabulary and semantics of business rules are specified. There is also outlined the current state of research on this topic. Then the definition and formalization of business rules using semantics and business vocabulary is described. Based on these proposed procedures was created a tool that implements and simulate these processes. The main advantage of this tool is “Business Rules Layer”, which implements business rules into the system but is separated from this system. Source code of the rules and the system are not mixed together. Finally, the results are evaluated and future development is suggested.

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

Science.gov (United States)

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.

Semantic integration of information about orthologs and diseases: the OGO system.

Science.gov (United States)

Miñarro-Gimenez, Jose Antonio; Egaña Aranguren, Mikel; Martínez Béjar, Rodrigo; Fernández-Breis, Jesualdo Tomás; Madrid, Marisa

2011-12-01

Semantic Web technologies like RDF and OWL are currently applied in life sciences to improve knowledge management by integrating disparate information. Many of the systems that perform such task, however, only offer a SPARQL query interface, which is difficult to use for life scientists. We present the OGO system, which consists of a knowledge base that integrates information of orthologous sequences and genetic diseases, providing an easy to use ontology-constrain driven query interface. Such interface allows the users to define SPARQL queries through a graphical process, therefore not requiring SPARQL expertise. Copyright © 2011 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2010-07-01

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

Semantic Approaches for Knowledge Discovery and Retrieval in Biomedicine

DEFF Research Database (Denmark)

Wilkowski, Bartlomiej

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

Mapping Between Semantic Graphs and Sentences in Grammar Induction System

Directory of Open Access Journals (Sweden)

Laszlo Kovacs

2010-06-01

Full Text Available The proposed transformation module performs mapping be-
tween two di®erent knowledge representation forms used in grammar induction systems. The kernel knowledge representation form is a special predicate centered conceptual graph called ECG. The ECG provides a semantic-based, language independent description of the environment. The other base representation form is some kind of language. The sentences of the language should meet the corresponding grammatical rules. The pilot project demonstrates the functionality of a translator module using this transformation engine between the ECG graph and the Hungarian language.

Semantic memory in object use.

Science.gov (United States)

Silveri, Maria Caterina; Ciccarelli, Nicoletta

2009-10-01

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

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

Science.gov (United States)

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

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

Science.gov (United States)

Wiese, Holger

2011-11-01

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

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.

Improving life sciences information retrieval using semantic web technology.

Science.gov (United States)

Quan, Dennis

2007-05-01

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

Semantic Indexing of Medical Learning Objects: Medical Students' Usage of a Semantic Network.

Science.gov (United States)

Tix, Nadine; Gießler, Paul; Ohnesorge-Radtke, Ursula; Spreckelsen, Cord

2015-11-11

The Semantically Annotated Media (SAM) project aims to provide a flexible platform for searching, browsing, and indexing medical learning objects (MLOs) based on a semantic network derived from established classification systems. Primarily, SAM supports the Aachen emedia skills lab, but SAM is ready for indexing distributed content and the Simple Knowledge Organizing System standard provides a means for easily upgrading or even exchanging SAM's semantic network. There is a lack of research addressing the usability of MLO indexes or search portals like SAM and the user behavior with such platforms. The purpose of this study was to assess the usability of SAM by investigating characteristic user behavior of medical students accessing MLOs via SAM. In this study, we chose a mixed-methods approach. Lean usability testing was combined with usability inspection by having the participants complete four typical usage scenarios before filling out a questionnaire. The questionnaire was based on the IsoMetrics usability inventory. Direct user interaction with SAM (mouse clicks and pages accessed) was logged. The study analyzed the typical usage patterns and habits of students using a semantic network for accessing MLOs. Four scenarios capturing characteristics of typical tasks to be solved by using SAM yielded high ratings of usability items and showed good results concerning the consistency of indexing by different users. Long-tail phenomena emerge as they are typical for a collaborative Web 2.0 platform. Suitable but nonetheless rarely used keywords were assigned to MLOs by some users. It is possible to develop a Web-based tool with high usability and acceptance for indexing and retrieval of MLOs. SAM can be applied to indexing multicentered repositories of MLOs collaboratively.

Knowledge represented using RDF semantic network in the concept of semantic web

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Lukasova, A., E-mail: alena.lukasova@osu.cz; Vajgl, M., E-mail: marek.vajgl@osu.cz; Zacek, M., E-mail: martin.zacek@osu.cz [Department of Informatics and Computers, Faculty of Science, University of Ostrava 30. dubna 22, 701 03 Ostrava, Czech Republic http://prf.osu.eu/kip/ (Czech Republic)

2016-06-08

The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDF to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.

Knowledge represented using RDF semantic network in the concept of semantic web

International Nuclear Information System (INIS)

Lukasova, A.; Vajgl, M.; Zacek, M.

2016-01-01

The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDF to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.

Semi-Supervised Learning to Identify UMLS Semantic Relations.

Science.gov (United States)

Luo, Yuan; Uzuner, Ozlem

2014-01-01

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

Impact of Semantic Relatedness on Associative Memory: An ERP Study

Directory of Open Access Journals (Sweden)

Pierre Desaunay

2017-06-01

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

SPARK: Adapting Keyword Query to Semantic Search

Science.gov (United States)

Zhou, Qi; Wang, Chong; Xiong, Miao; Wang, Haofen; Yu, Yong

Semantic search promises to provide more accurate result than present-day keyword search. However, progress with semantic search has been delayed due to the complexity of its query languages. In this paper, we explore a novel approach of adapting keywords to querying the semantic web: the approach automatically translates keyword queries into formal logic queries so that end users can use familiar keywords to perform semantic search. A prototype system named 'SPARK' has been implemented in light of this approach. Given a keyword query, SPARK outputs a ranked list of SPARQL queries as the translation result. The translation in SPARK consists of three major steps: term mapping, query graph construction and query ranking. Specifically, a probabilistic query ranking model is proposed to select the most likely SPARQL query. In the experiment, SPARK achieved an encouraging translation result.

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

Science.gov (United States)

Uthayan, K R; Mala, G S Anandha

2015-01-01

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

Development of a semantically operating risk management information system using the example of the European organization for nuclear research (CERN)

International Nuclear Information System (INIS)

Aprin, Lars

2013-01-01

The term risk analysis summarises the systematic endeavour to identify and evaluate the risks within an organisation associated with projects and actions, and make it possible to regulate risks. Risk analyses are an integral component of risk management, and thus essential to consolidating safety. In that respect, the adequacy and reliability of the findings obtained by way of risk analysis directly depend on the availability and quality of the knowledge resources supplied organisationally. Access to knowledge relevant to making decisions is, however, hampered, in the real world of work through the impact of various informational barriers. Knowledge that is conducive to understanding and avoiding risks is frequently stored in very specialised database systems, the individual syntactic and semantic structures of which make it a very time-consuming and laborious operation to use such knowledge in the context of applications other than the one originally linked to the databases. In addition, a degree of ambiguity that accompanies the semi-structured nature of many documentation and reporting systems makes it difficult to process knowledge efficiently and in an automated way, for example in conjunction with search engines. This dissertation presents a contribution towards overcoming the existing knowledge barriers in risk management. To this end, the method of applying semantic methods of representing knowledge in the domain of risk analysis is proposed. The focus is on the semantic web, which -as an enhancement of the World Wide Web- makes it possible to explicitly grasp the meaning of knowledge contexts and reproduce this information. Should the present risk management be distinguished by document-based organisation and distribution of knowledge, the semantic web presents methods and tools which make it possible to put the knowledge directly to work on the data set level. Building on the latter, the concept of a semantically operating risk management information

The role of orthography in the semantic activation of neighbors.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2013-07-01

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

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.

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

From Data to Semantic Information

Directory of Open Access Journals (Sweden)

Luciano Floridi

2003-06-01

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

The effects of semantic congruency: a research of audiovisual P300-speller.

Science.gov (United States)

Cao, Yong; An, Xingwei; Ke, Yufeng; Jiang, Jin; Yang, Hanjun; Chen, Yuqian; Jiao, Xuejun; Qi, Hongzhi; Ming, Dong

2017-07-25

Over the past few decades, there have been many studies of aspects of brain-computer interface (BCI). Of particular interests are event-related potential (ERP)-based BCI spellers that aim at helping mental typewriting. Nowadays, audiovisual unimodal stimuli based BCI systems have attracted much attention from researchers, and most of the existing studies of audiovisual BCIs were based on semantic incongruent stimuli paradigm. However, no related studies had reported that whether there is difference of system performance or participant comfort between BCI based on semantic congruent paradigm and that based on semantic incongruent paradigm. The goal of this study was to investigate the effects of semantic congruency in system performance and participant comfort in audiovisual BCI. Two audiovisual paradigms (semantic congruent and incongruent) were adopted, and 11 healthy subjects participated in the experiment. High-density electrical mapping of ERPs and behavioral data were measured for the two stimuli paradigms. The behavioral data indicated no significant difference between congruent and incongruent paradigms for offline classification accuracy. Nevertheless, eight of the 11 participants reported their priority to semantic congruent experiment, two reported no difference between the two conditions, and only one preferred the semantic incongruent paradigm. Besides, the result indicted that higher amplitude of ERP was found in incongruent stimuli based paradigm. In a word, semantic congruent paradigm had a better participant comfort, and maintained the same recognition rate as incongruent paradigm. Furthermore, our study suggested that the paradigm design of spellers must take both system performance and user experience into consideration rather than merely pursuing a larger ERP response.

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)

Semantic web implications for technologies and business practices

CERN Document Server

2016-01-01

This book examines recent developments in semantic systems that can respond to situations and environments and events. The contributors to this book cover how to design, implement, and utilize disruptive technologies from the semantic and Web 3.0 arena. The editor and the contributors discuss two fundamental sets of disruptive technologies: the development of semantic technologies including description logics, ontologies, and agent frameworks; and the development of semantic information rendering including graphical forms of displays of high-density time-sensitive data to improve situational awareness. Beyond practical illustrations of emerging technologies, the goal of this book is to help readers learn about managing information resources in new ways and reinforcing the learning as they read on.   ·         Examines the contrast of competing paradigms and approaches to problem solving and decision-making using technology tools and techniques ·         Covers how to use semantic principle...

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

Use of Semantic Web technologies for data management in the Earth sciences (and beyond) has great potential but is still in its early stages, since the challenges of translating data into a more explicit or semantic form for immediate use within applications has not been fully addressed. In this abstract we help address this challenge by introducing the SemantEco Annotator, which enables anyone, regardless of expertise, to semantically annotate tabular Earth Science data and translate it into linked data format, while applying the logic inherent in community-standard vocabularies to guide the process. The Annotator was conceived under a desire to unify dataset content from a variety of sources under common vocabularies, for use in semantically-enabled web applications. Our current use case employs linked data generated by the Annotator for use in the SemantEco environment, which utilizes semantics to help users explore, search, and visualize water or air quality measurement and species occurrence data through a map-based interface. The generated data can also be used immediately to facilitate discovery and search capabilities within 'big data' environments. The Annotator provides a method for taking information about a dataset, that may only be known to its maintainers, and making it explicit, in a uniform and machine-readable fashion, such that a person or information system can more easily interpret the underlying structure and meaning. Its primary mechanism is to enable a user to formally describe how columns of a tabular dataset relate and/or describe entities. For example, if a user identifies columns for latitude and longitude coordinates, we can infer the data refers to a point that can be plotted on a map. Further, it can be made explicit that measurements of 'nitrate' and 'NO3-' are of the same entity through vocabulary assignments, thus more easily utilizing data sets that use different nomenclatures. The Annotator provides an extensive and searchable

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

DOORS to the semantic web and grid with a PORTAL for biomedical computing.

Science.gov (United States)

Taswell, Carl

2008-03-01

The semantic web remains in the early stages of development. It has not yet achieved the goals envisioned by its founders as a pervasive web of distributed knowledge and intelligence. Success will be attained when a dynamic synergism can be created between people and a sufficient number of infrastructure systems and tools for the semantic web in analogy with those for the original web. The domain name system (DNS), web browsers, and the benefits of publishing web pages motivated many people to register domain names and publish web sites on the original web. An analogous resource label system, semantic search applications, and the benefits of collaborative semantic networks will motivate people to register resource labels and publish resource descriptions on the semantic web. The Domain Ontology Oriented Resource System (DOORS) and Problem Oriented Registry of Tags and Labels (PORTAL) are proposed as infrastructure systems for resource metadata within a paradigm that can serve as a bridge between the original web and the semantic web. The Internet Registry Information Service (IRIS) registers [corrected] domain names while DNS publishes domain addresses with mapping of names to addresses for the original web. Analogously, PORTAL registers resource labels and tags while DOORS publishes resource locations and descriptions with mapping of labels to locations for the semantic web. BioPORT is proposed as a prototype PORTAL registry specific for the problem domain of biomedical computing.

Bridging the semantic gap in sports

Science.gov (United States)

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

2003-01-01

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

Practical Experiences for the Development of Educational Systems in the Semantic Web

Science.gov (United States)

Sánchez Vera, Ma. del Mar; Tomás Fernández Breis, Jesualdo; Serrano Sánchez, José Luis; Prendes Espinosa, Ma. Paz

2013-01-01

Semantic Web technologies have been applied in educational settings for different purposes in recent years, with the type of application being mainly defined by the way in which knowledge is represented and exploited. The basic technology for knowledge representation in Semantic Web settings is the ontology, which represents a common, shareable…

Semantic Document Model to Enhance Data and Knowledge Interoperability

Science.gov (United States)

Nešić, Saša

To enable document data and knowledge to be efficiently shared and reused across application, enterprise, and community boundaries, desktop documents should be completely open and queryable resources, whose data and knowledge are represented in a form understandable to both humans and machines. At the same time, these are the requirements that desktop documents need to satisfy in order to contribute to the visions of the Semantic Web. With the aim of achieving this goal, we have developed the Semantic Document Model (SDM), which turns desktop documents into Semantic Documents as uniquely identified and semantically annotated composite resources, that can be instantiated into human-readable (HR) and machine-processable (MP) forms. In this paper, we present the SDM along with an RDF and ontology-based solution for the MP document instance. Moreover, on top of the proposed model, we have built the Semantic Document Management System (SDMS), which provides a set of services that exploit the model. As an application example that takes advantage of SDMS services, we have extended MS Office with a set of tools that enables users to transform MS Office documents (e.g., MS Word and MS PowerPoint) into Semantic Documents, and to search local and distant semantic document repositories for document content units (CUs) over Semantic Web protocols.

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

Science.gov (United States)

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.

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

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

Semantics for Communicating Actors with Interdependent Real-Time Deadlines

DEFF Research Database (Denmark)

Knoll, Istvan; Ravn, Anders Peter; Skou, Arne

2009-01-01

on the results, these tools must use consistent semantics for the model. Yet, a monolithic semantic model is just as complex as the entity it describes. In order to circumvent this issue, we define a three level semantics giving independent definitions of the functionality of actors, the temporal properties...... of communications, and finally imposing deadlines on the timing of dependent actors. With this approach the semantics is used directly in developing a simulator supporting the nondeterminism of the abstract semantics such that e.g. potential race conditions can be detected. The layers are also planned to underpin...... independent specialized verification tools. The verification task for timed, hybrid systems can thus be divided into the continuous, discrete, and timing domains with automated translation to specialized tools, and this promises better scalability than simulation or model checking of one complex model....

Evaluation of the Project Management Competences Based on the Semantic Networks

Directory of Open Access Journals (Sweden)

Constanta Nicoleta BODEA

2008-01-01

Full Text Available The paper presents the testing and evaluation facilities of the SinPers system. The SinPers is a web based learning environment in project management, capable of building and conducting a complete and personalized training cycle, from the definition of the learning objectives to the assessment of the learning results for each learner. The testing and evaluation facilities of SinPers system are based on the ontological approach. The educational ontology is mapped on a semantic network. Further, the semantic network is projected into a concept space graph. The semantic computability of the concept space graph is used to design the tests. The paper focuses on the applicability of the system in the certification, for the knowledge assessment, related to each element of competence. The semantic computability is used for differentiating between different certification levels.

Methods and apparatus for multi-resolution replication of files in a parallel computing system using semantic information

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Faibish, Sorin; Bent, John M.; Tzelnic, Percy; Grider, Gary; Torres, Aaron

2015-10-20

Techniques are provided for storing files in a parallel computing system using different resolutions. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a sub-file. The method comprises the steps of obtaining semantic information related to the file; generating a plurality of replicas of the file with different resolutions based on the semantic information; and storing the file and the plurality of replicas of the file in one or more storage nodes of the parallel computing system. The different resolutions comprise, for example, a variable number of bits and/or a different sub-set of data elements from the file. A plurality of the sub-files can be merged to reproduce the file.

Towards an Approach of Semantic Access Control for Cloud Computing

Science.gov (United States)

Hu, Luokai; Ying, Shi; Jia, Xiangyang; Zhao, Kai

With the development of cloud computing, the mutual understandability among distributed Access Control Policies (ACPs) has become an important issue in the security field of cloud computing. Semantic Web technology provides the solution to semantic interoperability of heterogeneous applications. In this paper, we analysis existing access control methods and present a new Semantic Access Control Policy Language (SACPL) for describing ACPs in cloud computing environment. Access Control Oriented Ontology System (ACOOS) is designed as the semantic basis of SACPL. Ontology-based SACPL language can effectively solve the interoperability issue of distributed ACPs. This study enriches the research that the semantic web technology is applied in the field of security, and provides a new way of thinking of access control in cloud computing.

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.

Visual Development Environment for Semantically Interoperable Smart Cities Applications

OpenAIRE

Roukounaki , Aikaterini; Soldatos , John; Petrolo , Riccardo; Loscri , Valeria; Mitton , Nathalie; Serrano , Martin

2015-01-01

International audience; This paper presents an IoT architecture for the semantic interoperability of diverse IoT systems and applications in smart cities. The architecture virtualizes diverse IoT systems and ensures their modelling and representation according to common standards-based IoT ontologies. Furthermore, based on this architecture, the paper introduces a first-of-a-kind visual development environment which eases the development of semantically interoperable applications in smart cit...

Lack of semantic priming effects in famous person recognition in Mild Cognitive Impairment.

Science.gov (United States)

Brambati, Simona M; Peters, Frédéric; Belleville, Sylvie; Joubert, Sven

2012-04-01

Growing evidence indicates that individuals with Mild Cognitive Impairment (MCI) manifest semantic deficits that are often more severe for items that are characterized by a unique semantic and lexical association, such as famous people and famous buildings, than common concepts, such as objects. However, it is still controversial whether the semantic deficits observed in MCI are determined by a degradation of semantic information or by a deficit in intentional access to semantic knowledge. Here we used a semantic priming task in order to assess the integrity of the semantic system without requiring explicit access to this system. This paradigm may provide new insights in clarifying the nature of the semantic deficits in MCI. We assessed the semantic and repetition priming effect in 13 individuals with MCI and 13 age-matched controls who engaged in a familiarity judgment task of famous names. In the semantic priming condition, the prime was the name of a member of the same occupation category as the target (Tom Cruise-Brad Pitt), while in the repetition priming condition the prime was the same name as the target (Charlie Chaplin-Charlie Chaplin). The results showed a defective priming effect in MCI in the semantic but not in the repetition priming condition. Specifically, when compared to controls, MCI patients did not show a facilitation effect in responding to the same occupation prime-target pairs, but they showed an equivalent facilitation effect when the target was the same name as the prime. The present results provide support to the hypothesis that the semantic impairments observed in MCI cannot be uniquely ascribed to a deficit in intentional access to semantic information. Instead, these findings point to the semantic nature of these deficits and, in particular, to a degraded representation of semantic information concerning famous people. Copyright © 2011 Elsevier Srl. All rights reserved.

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

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.

Shared Semantics and the Use of Organizational Memories for E-Mail Communications.

Science.gov (United States)

Schwartz, David G.

1998-01-01

Examines the use of shared semantics information to link concepts in an organizational memory to e-mail communications. Presents a framework for determining shared semantics based on organizational and personal user profiles. Illustrates how shared semantics are used by the HyperMail system to help link organizational memories (OM) content to…

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

Science.gov (United States)

2011-01-01

preservation of data correspondence and provenance. Our representation builds on existing cheminformatics technologies and, by the virtue of RDF specification, remains flexible and amenable to application- and domain-specific annotations without compromising chemical data integration. We conclude that the adoption of a consistent and semantically-enabled chemical specification is imperative for surviving the coming chemical data deluge and supporting systems science research. PMID:21595881

Intelligence related upper alpha desynchronization in a semantic memory task.

Science.gov (United States)

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

2005-07-30

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

SEMANTIC DERIVATION OF BORROWINGS

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Shigapova, F.F.

2017-09-01

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

Subliminal semantic priming in speech.

Directory of Open Access Journals (Sweden)

Jérôme Daltrozzo

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

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.

A Novel Relevance Feedback Approach Based on Similarity Measure Modification in an X-Ray Image Retrieval System Based on Fuzzy Representation Using Fuzzy Attributed Relational Graph

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Hossien Pourghassem

2011-04-01

Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.

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

Science.gov (United States)

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

Science.gov (United States)

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

Academic Program Administration via Semantic Web – A Case Study

OpenAIRE

Qurban A Memon; Shakeel A. Khoja

2009-01-01

Generally, administrative systems in an academic environment are disjoint and support independent queries. The objective in this work is to semantically connect these independent systems to provide support to queries run on the integrated platform. The proposed framework, by enriching educational material in the legacy systems, provides a value-added semantics layer where activities such as annotation, query and reasoning can be carried out to support management requirements. We discuss the d...

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…

Incorporating Semantic Knowledge into Dynamic Data Processing for Smart Power Grids

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor

2012-11-15

Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require continuous information monitoring and integration present novel opportunities and challenges for Semantic Web technologies. Semantic Web is promising to model diverse Smart Grid domain knowledge for enhanced situation awareness and response by multi-disciplinary participants. However, current technology does pose a performance overhead for dynamic analysis of sensor measurements. In this paper, we combine semantic web and complex event processing for stream based semantic querying. We illustrate its adoption in the USC Campus Micro-Grid for detecting and enacting dynamic response strategies to peak power situations by diverse user roles. We also describe the semantic ontology and event query model that supports this. Further, we introduce and evaluate caching techniques to improve the response time for semantic event queries to meet our application needs and enable sustainable energy management.

Operationalizing Semantic Medline for meeting the information needs at point of care

Science.gov (United States)

Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

2015-01-01

Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible. PMID:26306259

Operationalizing Semantic Medline for meeting the information needs at point of care.

Science.gov (United States)

Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

2015-01-01

Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible.

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.…

Quality Assurance of UMLS Semantic Type Assignments Using SNOMED CT Hierarchies.

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Gu, H; Chen, Y; He, Z; Halper, M; Chen, L

2016-01-01

The Unified Medical Language System (UMLS) is one of the largest biomedical terminological systems, with over 2.5 million concepts in its Metathesaurus repository. The UMLS's Semantic Network (SN) with its collection of 133 high-level semantic types serves as an abstraction layer on top of the Metathesaurus. In particular, the SN elaborates an aspect of the Metathesaurus's concepts via the assignment of one or more types to each concept. Due to the scope and complexity of the Metathesaurus, errors are all but inevitable in this semantic-type assignment process. To develop a semi-automated methodology to help assure the quality of semantic-type assignments within the UMLS. The methodology uses a cross-validation strategy involving SNOMED CT's hierarchies in combination with UMLS semantic types. Semantically uniform, disjoint concept groups are generated programmatically by partitioning the collection of all concepts in the same SNOMED CT hierarchy according to their respective semantic-type assignments in the UMLS. Domain experts are then called upon to review the concepts in any group having a small number of concepts. It is our hypothesis that a semantic-type assignment combination applicable only to a very small number of concepts in a SNOMED CT hierarchy is an indicator of potential problems. The methodology was applied to the UMLS 2013AA release along with the SNOMED CT from January 2013. An overall error rate of 33% was found for concepts proposed by the quality-assurance methodology. Supporting our hypothesis, that number was four times higher than the error rate found in control samples. The results show that the quality-assurance methodology can aid in effective and efficient identification of UMLS semantic-type assignment errors.

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.

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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).

Semantics of probabilistic processes an operational approach

CERN Document Server

Deng, Yuxin

2015-01-01

This book discusses the semantic foundations of concurrent systems with nondeterministic and probabilistic behaviour. Particular attention is given to clarifying the relationship between testing and simulation semantics and characterising bisimulations from metric, logical, and algorithmic perspectives. Besides presenting recent research outcomes in probabilistic concurrency theory, the book exemplifies the use of many mathematical techniques to solve problems in computer science, which is intended to be accessible to postgraduate students in Computer Science and Mathematics. It can also be us

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.

RoboDB: an application of Semantic Web Technologies to robotics

NARCIS (Netherlands)

Juarez, Alex; Hu, J.; Feijs, L.M.G.

2011-01-01

RoboDB is a knowledge acquisition system that gathers information about robots. RoboDB uses Semantic Web technologies and tools to help the user in creating semantic descriptions of robot embodiments and their capabilities, as well as in building an ontology of robotics projects, research

A model-driven approach for representing clinical archetypes for Semantic Web environments.

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Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás; Maldonado, José Alberto

2009-02-01

The life-long clinical information of any person supported by electronic means configures his Electronic Health Record (EHR). This information is usually distributed among several independent and heterogeneous systems that may be syntactically or semantically incompatible. There are currently different standards for representing and exchanging EHR information among different systems. In advanced EHR approaches, clinical information is represented by means of archetypes. Most of these approaches use the Archetype Definition Language (ADL) to specify archetypes. However, ADL has some drawbacks when attempting to perform semantic activities in Semantic Web environments. In this work, Semantic Web technologies are used to specify clinical archetypes for advanced EHR architectures. The advantages of using the Ontology Web Language (OWL) instead of ADL are described and discussed in this work. Moreover, a solution combining Semantic Web and Model-driven Engineering technologies is proposed to transform ADL into OWL for the CEN EN13606 EHR architecture.

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

From Science to e-Science to Semantic e-Science: A Heliosphysics Case Study

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Narock, Thomas; Fox, Peter

2011-01-01

The past few years have witnessed unparalleled efforts to make scientific data web accessible. The Semantic Web has proven invaluable in this effort; however, much of the literature is devoted to system design, ontology creation, and trials and tribulations of current technologies. In order to fully develop the nascent field of Semantic e-Science we must also evaluate systems in real-world settings. We describe a case study within the field of Heliophysics and provide a comparison of the evolutionary stages of data discovery, from manual to semantically enable. We describe the socio-technical implications of moving toward automated and intelligent data discovery. In doing so, we highlight how this process enhances what is currently being done manually in various scientific disciplines. Our case study illustrates that Semantic e-Science is more than just semantic search. The integration of search with web services, relational databases, and other cyberinfrastructure is a central tenet of our case study and one that we believe has applicability as a generalized research area within Semantic e-Science. This case study illustrates a specific example of the benefits, and limitations, of semantically replicating data discovery. We show examples of significant reductions in time and effort enable by Semantic e-Science; yet, we argue that a "complete" solution requires integrating semantic search with other research areas such as data provenance and web services.

Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases.

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Kobayashi, Norio; Ishii, Manabu; Takahashi, Satoshi; Mochizuki, Yoshiki; Matsushima, Akihiro; Toyoda, Tetsuro

2011-07-01

Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org.

E-Learning System Overview Based on Semantic Web

Science.gov (United States)

Alsultanny, Yas A.

2006-01-01

The challenge of the semantic web is the provision of distributed information with well-defined meaning, understandable for different parties. e-Learning is efficient task relevant and just-in-time learning grown from the learning requirements of the new dynamically changing, distributed business world. In this paper we design an e-Learning system…

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”.

Exploring the role of the posterior middle temporal gyrus in semantic cognition: Integration of anterior temporal lobe with executive processes.

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Davey, James; Thompson, Hannah E; Hallam, Glyn; Karapanagiotidis, Theodoros; Murphy, Charlotte; De Caso, Irene; Krieger-Redwood, Katya; Bernhardt, Boris C; Smallwood, Jonathan; Jefferies, Elizabeth

2016-08-15

Making sense of the world around us depends upon selectively retrieving information relevant to our current goal or context. However, it is unclear whether selective semantic retrieval relies exclusively on general control mechanisms recruited in demanding non-semantic tasks, or instead on systems specialised for the control of meaning. One hypothesis is that the left posterior middle temporal gyrus (pMTG) is important in the controlled retrieval of semantic (not non-semantic) information; however this view remains controversial since a parallel literature links this site to event and relational semantics. In a functional neuroimaging study, we demonstrated that an area of pMTG implicated in semantic control by a recent meta-analysis was activated in a conjunction of (i) semantic association over size judgements and (ii) action over colour feature matching. Under these circumstances the same region showed functional coupling with the inferior frontal gyrus - another crucial site for semantic control. Structural and functional connectivity analyses demonstrated that this site is at the nexus of networks recruited in automatic semantic processing (the default mode network) and executively demanding tasks (the multiple-demand network). Moreover, in both task and task-free contexts, pMTG exhibited functional properties that were more similar to ventral parts of inferior frontal cortex, implicated in controlled semantic retrieval, than more dorsal inferior frontal sulcus, implicated in domain-general control. Finally, the pMTG region was functionally correlated at rest with other regions implicated in control-demanding semantic tasks, including inferior frontal gyrus and intraparietal sulcus. We suggest that pMTG may play a crucial role within a large-scale network that allows the integration of automatic retrieval in the default mode network with executively-demanding goal-oriented cognition, and that this could support our ability to understand actions and non

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

KAUST Repository

Hoehndorf, Robert

2015-02-19

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, druggable therapeutic targets, and determination of pathogenicity. Results: We have developed PhenomeNET 2, a system that enables similarity-based searches over a large repository of phenotypes in real-time. It can be used to identify strains of model organisms that are phenotypically similar to human patients, diseases that are phenotypically similar to model organism phenotypes, or drug effect profiles that are similar to the phenotypes observed in a patient or model organism. PhenomeNET 2 is available at http://aber-owl.net/phenomenet. Conclusions: Phenotype-similarity searches can provide a powerful tool for the discovery and investigation of molecular mechanisms underlying an observed phenotypic manifestation. PhenomeNET 2 facilitates user-defined similarity searches and allows researchers to analyze their data within a large repository of human, mouse and rat phenotypes.

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.

Requirements-level semantics and model checking of object-oriented statecharts

NARCIS (Netherlands)

Eshuis, H.; Jansen, D.N.; Wieringa, Roelf J.

2002-01-01

In this paper we define a requirements-level execution semantics for object-oriented statecharts and show how properties of a system specified by these statecharts can be model checked using tool support for model checkers. Our execution semantics is requirements-level because it uses the perfect

Practical experiences for the development of educational sys-tems in the semantic web

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Mª del Mar Sánchez Vera

2013-01-01

Full Text Available Semantic Web technologies have been applied in educational settings for different purposes in recent years, with the type of application being mainly defined by the way in which knowledge is represented and exploited. The basic technology for knowledge representation in Semantic Web settings is the ontology, which represents a common, shareable and reusable view of a particular application domain. Ontologies can support different activities in educational settings such as organizing course contents, classifying learning objects or assessing learning levels. Consequently, ontologies can become a very useful tool from a pedagogical perspective. This paper focuses on two different experiences where Semantic Web technologies are used in educational settings, the difference between them lying in how knowledge is obtained and represented. On the one hand, the OeLE platform uses ontologies as a support for assessment processes. Such ontologies have to be designed and implemented in semantic languages apt to be used by OeLE. On the other hand, the ENSEMBLE project pursues the development of semantic web applications by creating specific knowledge representations drawn from user needs. Our paper is consequently going to offer an in-depth analysis of the role played by ontologies, showing how they can be used in different ways drawing a comparison between model patterns and examining the ways in which they can complement each other as well as their practical implications

Measuring Semantic and Structural Information for Data Oriented Workflow Retrieval with Cost Constraints

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