Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/38799
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dc.contributor.authorQuesada-Martínez, Manuel-
dc.contributor.authorFernández-Breis, Jesualdo Tomás-
dc.contributor.authorStevens, Robert-
dc.contributor.otherDepartamentos de la UMH::Estadística, Matemáticas e Informáticaes_ES
dc.date.accessioned2025-12-15T08:58:09Z-
dc.date.available2025-12-15T08:58:09Z-
dc.date.created2015-04-
dc.identifier.citationCurrent Bioinformatics, Vol. 10, Nº 2 (2015)es_ES
dc.identifier.issn2212-392X-
dc.identifier.issn1574-8936-
dc.identifier.urihttps://hdl.handle.net/11000/38799-
dc.description.abstractHundreds of biomedical ontologies have been produced, with many of the significant, widely used ones being developed in collaborative efforts and following a set of construction principles, which include using a systematic naming convention for their labels. Despite their success, many of these ontologies have lacked a foundation of axioms that would expose the wealth of knowledge in the ontologies to computational reasoning. Our previous results suggest that exploiting the structure on the labels may contribute to an axiomatic enrichment. Hence, in this work we perform a study of the structure of the labels of the ontologies available in BioPortal to classify them in terms of potential interest for axiomatic enrichment.es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherBentham Science Publisherses_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAnnotationses_ES
dc.subjectBiomedical ontologieses_ES
dc.subjectLexical analysises_ES
dc.subjectOntology labelses_ES
dc.subjectOWLes_ES
dc.subjectRe-usees_ES
dc.titleLexical characterization of bio-ontologies by the inspection of regularities in labelses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.2174/157489361002150518124739es_ES
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Artículos - Estadística, Matemáticas e Informática


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