Search results for "Semantic similarity"

showing 10 items of 38 documents

Ontology-based service matching and discovery

2011

In this paper we consider ontologies as knowledge structures that specify attributes of services, their properties and relations among them to enable finding semantic similarity between service descriptions and service requests. Ontologies reflect semantic relationship between concepts represented by attributes in service descriptions and service requests. We use knowledge from ontologies to enhance the both user service requests and service descriptions by adding concepts that are not presented in the original descriptions, and use them in comparison process. It results in more precise matching since we consider also implicit concepts. Thus services and requests that do not contain exact m…

Service (business)World Wide WebMatching (statistics)Information retrievalSemantic similarityComputer scienceService discoveryOntology (information science)Web serviceSemanticscomputer.software_genreOntology alignmentcomputerProceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems
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A Semantic Similarity Measure for the SIMS Framework

2008

The amount of currently available digital information grows rapidly. Relevant information is often spread over different information sources. An efficient and flexible framework to allow users to satisfy ef- fectively their information needs is required. The work presented in this paper describes SIMS (Semantic Information Management System), a ref- erence architecture for a framework performing semantic annotation, search and retrieval of information from multiple sources. The work pre- sented in this paper focuses on a specific SIMS module, the SIMS Semantic Content Navigator, proposing an algorithm and the related implementa- tion to calculate a semantic similarity measure inside an OWL …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalComputer scienceInformation needsWeb Ontology Languageknowledge managementOntology (information science)Semantic gridSemantic similaritySemantic similarityExplicit semantic analysisSemantic computingOntologySemantic technologySemantic integrationontologySemantic Web StackcomputerInformation filtering systemcomputer.programming_language
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An A* Based Semantic Tokenizer for Increasing the Performance of Semantic Applications

2013

Semantic Applications (SAs) makes use of ontolo- gies and their performance can depend on the syntactic labels of the modeled entities; even if several approaches have been devised to formalize ontologies, no formal approaches have been devised for naming their constituents, which look as long word concatenations without any particular separation. We present a novel semantic tokenizer that finds the sub-words through an application of the A* based search algorithm; the A* functions rely on a set of linguistic criteria and on the meta-cognitive perspective of the activity of reading.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalComputer sciencebusiness.industrySemantic searchOntology (information science)computer.software_genreSemantic tokenizer ontology A* tree search UIMASet (abstract data type)Semantic similaritySearch algorithmSemantic computingSemantic analyticsArtificial intelligencebusinesscomputerWord (computer architecture)Natural language processing2013 IEEE Seventh International Conference on Semantic Computing
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An ontology-based retrieval system for mammographic reports

2015

In healthcare domain it can be useful to compare unstructured free-text clinical reports in order to enable the search for similar and/or relevant clinical cases. In data mining and text analysis tasks, the cosine similarity is usually used for texts comparison purposes. It is usually performed by computing the standard document vector cosine similarity between the two vectors representing the report pair under analysis. In this paper a novel system based on text pre-processing techniques and a modelled medical knowledge, using an improved radiological ontology, is proposed. Medical terms organized in a hierarchical tree can assess semantic similarity relationships between unstructured repo…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalbusiness.industryComputer scienceOntology-based data integrationCosine similarityOntology (information science)SemanticsDomain (software engineering)Tree (data structure)Text miningMammography Reports Information Retrieval OntologySemantic similarityOntologyUpper ontologybusiness2015 IEEE Symposium on Computers and Communication (ISCC)
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A Combined Fuzzy Semantic Similarity Measure In Owl Ontologies

2008

An algorithm is presented in this paper to calculate a semantic similarity measure inside an OWL ontology. The formulation is based on a combined measure taking into account the two most important aspects involved in the similarity computation. These are the structural properties of a concept, and the information content inside the ontology. We define a fuzzy system to blend these information sources with a training process over some ontologies. Finding a similarity measure between concepts of an ontology is a fundamental topic to accomplish information exchange on the Web. Through this measure it is possible to perform sophisticated queries over the web where the user is able to request co…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniOWL ontologieFuzzy measureSemantic similarity measureSemantic Web
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Automatic Illustration of Short Texts via Web Images

2015

In this paper we propose a totally unsupervised and automatic illustration method, which aims to find onto the Web a set of images to illustrate the content of an input short text. The text is modelled as a semantic space and a set of relevant keywords is extracted. We compare and discuss different methods to create semantic representations by keyword extraction. Keywords are used to query Google Image Search engine for a list of relevant images. We also extract information from the Web pages that include the retrieved images, to create an Image Semantic Space, which is compared to the Text Semantic Space in order to rank the list of retrieved images. Tests showed that our method achieves v…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniWorld Wide WebMultimediaComputer scienceAutomatic Illustration Story Picturing Semantic Similarity Semantic Space Text Analysis Web Image Search Google Image.computer.software_genrecomputerProceedings of the 6th International Conference on Information Visualization Theory and Applications
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Syntagmatic and Paradigmatic Associations in Information Retrieval

2003

It is shown that unconscious associative processes taking place in the memory of a searcher during the formulation of a search query in information retrieval — such as the production of free word associations and the generation of synonyms — can be simulated using statistical models that analyze the distribution of words in large text corpora. The free word associations as produced by subjects on presentation of stimulus words can be predicted by applying first-order statistics to the frequencies of word co-occurrences as observed in texts. The generation of synonyms can also be conducted on co-occurrence data but requires second-order statistics. Both approaches are compared and validated …

Text corpusEmpirical dataSyntagmatic analysisInformation retrievalWeb search querySemantic similarityComputer scienceStatistical modelIndependent component analysisAssociative property
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Learning Similarity Scores by Using a Family of Distance Functions in Multiple Feature Spaces

2017

There exist a large number of distance functions that allow one to measure similarity between feature vectors and thus can be used for ranking purposes. When multiple representations of the same object are available, distances in each representation space may be combined to produce a single similarity score. In this paper, we present a method to build such a similarity ranking out of a family of distance functions. Unlike other approaches that aim to select the best distance function for a particular context, we use several distances and combine them in a convenient way. To this end, we adopt a classical similarity learning approach and face the problem as a standard supervised machine lea…

Training setbusiness.industryFeature vectorSimilarity heuristicPattern recognition02 engineering and technologyMachine learningcomputer.software_genreSemantic similarityArtificial Intelligence020204 information systemsNormalized compression distance0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceJaro–Winkler distancebusinesscomputerClassifier (UML)SoftwareSimilarity learningMathematicsInternational Journal of Pattern Recognition and Artificial Intelligence
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Toward Approximate GML Retrieval Based on Structural and Semantic Characteristics

2010

International audience; GML is emerging as the new standard for representing geographic information in GISs on the Web, allowing the encoding of structurally and semantically rich geographic data in self describing XML-based geographic entities. In this study, we address the problem of approximate querying and ranked results for GML data and provide a method for GML query evaluation. Our method consists of two main contributions. First, we propose a tree model for representing GML queries and data collections. Then, we introduce a GML retrieval method based on the concept of tree edit distance as an efficient means for comparing semi-structured data. Our approach allows the evaluation of bo…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Tree edit distanceSimilarity (geometry)[INFO.INFO-WB] Computer Science [cs]/WebComputer sciencecomputer.internet_protocol[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologycomputer.software_genre[SCCO.COMP] Cognitive science/Computer science020204 information systemsEncoding (memory)0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Information retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]GML SearchStructural & Semantic Similarity[INFO.INFO-WB]Computer Science [cs]/WebProcess (computing)[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]GISConstraint (information theory)[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Ranked retrieval020201 artificial intelligence & image processingData mining[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]computerXMLDecision tree model
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Qualifying semantic graphs using model checking

2011

International audience; Semantic interoperability problems have found their solutions using languages and techniques from the Semantic Web. The proliferation of ontologies and meta-information has improved the understanding of information and the relevance of search engine responses. However, the construction of semantic graphs is a source of numerous errors of interpretation or modeling and scalability remains a major problem. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border of two areas: the semantic web and the model checking. This line of research concerns t…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web0102 computer and information sciences02 engineering and technologycomputer.software_genre01 natural sciencesSocial Semantic Webtemporal logicSemantic similaritySemantic computing0202 electrical engineering electronic engineering information engineeringSemantic analyticsSemantic integrationSemantic Web StackInformation retrievalbusiness.industry[INFO.INFO-WB]Computer Science [cs]/WebSemantic search020207 software engineeringSemantic interoperability[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationModel-checking010201 computation theory & mathematicsSemantic graphTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS[INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationArtificial intelligencebusinesscomputerNatural language processing2011 International Conference on Innovations in Information Technology
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