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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.accessioned2026-01-27T12:49:01Z-
dc.date.available2026-01-27T12:49:01Z-
dc.date.created2013-
dc.identifier.citationArtificial Intelligence in Medicine - 14th Conference on Artificial Intelligence in Medicine, AIME 2013 (Proceedings)es_ES
dc.identifier.isbn978-3-642-38325-0-
dc.identifier.isbn978-3-642-38326-7-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttps://hdl.handle.net/11000/39031-
dc.descriptionSerie: Lecture Notes in Artificial Intelligence (LNAI) - 7885es_ES
dc.description.abstractThe increasing interest of the biomedical community in ontologies can be exemplified by the availability of hundreds of biomedical ontologies and controlled vocabularies, and by the international recommendations and efforts that suggest ontologies should play a critical role in the achievement of semantic interoperability in healthcare. However, many of the available biomedical ontologies are rich in human understandable labels, but are less rich in machine processable axioms, so their effectiveness for supporting advanced data analysis processes is limited. In this context, developing methods for analysing the labels and deriving axioms from them would contribute to make biomedical ontologies more useful. In fact, our recent work revealed that exploiting the regularities and structure of the labels could contribute to that axiomatic enrichment. In this paper, we present an approach for analysing and characterising biomedical ontologies from a lexical perspective, that is, by analysing the structure and content of the labels. This study has several goals: (1) characterization of the ontologies by the patterns found in their labels; (2) identifying which ones would be more appropriate for applying enrichment processes based on the labels; (3) inspecting how ontology re-use is being addressed for patterns found in more than one ontology. Our analysis method has been applied to BioPortal, which is likely to be the most popular repository of biomedical ontologies, containing more than two hundred resources. We have found that there is a high redundancy in the labels of the ontologies; it would be interesting to exploit the content and structure of the labels of many of them and that it seems that re-use is not always performed as it should be.es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBiomedical ontologieses_ES
dc.subjectOWLes_ES
dc.subjectOntology Engineeringes_ES
dc.subjectBioinformaticses_ES
dc.titleLexical Characterization and Analysis of the BioPortal Ontologieses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-642-38326-7_31es_ES
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Artículos - Estadística, Matemáticas e Informática


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