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dc.contributor.authorBerlanga Llavori, Rafael
dc.contributor.authorNebot Romero, María Victoria
dc.contributor.authorPérez Catalán, María
dc.date.accessioned2016-02-24T08:18:46Z
dc.date.available2016-02-24T08:18:46Z
dc.date.issued2015
dc.identifier.citationBERLANGA, Rafael; NEBOT, Victoria; PÉREZ, Maria. Tailored semantic annotation for semantic search. Web Semantics: Science, Services and Agents on the World Wide Web, 2015, vol. 30, p. 69-81ca_CA
dc.identifier.issn1570-8268
dc.identifier.urihttp://hdl.handle.net/10234/151507
dc.description.abstractThis paper presents a novel method for semantic annotation and search of a target corpus using several knowledge resources (KRs). This method relies on a formal statistical framework in which KR concepts and corpus documents are homogeneously represented using statistical language models. Under this framework, we can perform all the necessary operations for an efficient and effective semantic annotation of the corpus. Firstly, we propose a coarse tailoring of the KRs w.r.t the target corpus with the main goal of reducing the ambiguity of the annotations and their computational overhead. Then, we propose the generation of concept profiles, which allow measuring the semantic overlap of the KRs as well as performing a finer tailoring of them. Finally, we propose how to semantically represent documents and queries in terms of the KRs concepts and the statistical framework to perform semantic search. Experiments have been carried out with a corpus about web resources which includes several Life Sciences catalogs and Wikipedia pages related to web resources in general (e.g., databases, tools, services, etc.). Results demonstrate that the proposed method is more effective and efficient than state-of-the-art methods relying on either context-free annotation or keyword-based search.ca_CA
dc.description.sponsorShipWe thank anonymous reviewers for their very useful comments and suggestions. The work was supported by the CICYT project TIN2011-24147 from the Spanish Ministry of Economy and Competitiveness (MINECO).ca_CA
dc.format.extent13 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherElsevierca_CA
dc.relation.isPartOfWeb Semantics: Science, Services and Agents on the World Wide Web, 2015, vol. 30ca_CA
dc.rightsCopyright © Elsevierca_CA
dc.subjectSemantic annotationca_CA
dc.subjectSemantic searchca_CA
dc.subjectLanguage modelsca_CA
dc.titleTailored semantic annotation for semantic searchca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1016/j.websem.2014.07.007
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttp://www.sciencedirect.com/science/article/pii/S1570826814000559ca_CA


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  • LSI_Articles [264]
    Articles de publicacions periòdiques escrits per professors del Departament de Llenguatges i Sistemes Informàtics

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