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dc.contributor.authorMorente-Molinera, Juan Antonio (1)
dc.contributor.authorPerez, I. J.
dc.contributor.authorCabrerizo, Francisco Javier
dc.contributor.authorPorcel, Carlos
dc.contributor.authorHerrera-Viedma, Enrique
dc.date2016
dc.date.accessioned2020-04-16T11:10:16Z
dc.date.available2020-04-16T11:10:16Z
dc.identifier.isbn9781509018970
dc.identifier.issn1062-922X
dc.identifier.urihttps://reunir.unir.net/handle/123456789/9972
dc.description.abstractThe appearance of Fuzzy Ontologies has improved the way that crisp ontologies use to represent information. Thanks to them, it is possible to represent information in an imprecise and linguistic way using linguistic modelling and fuzzy sets. Nevertheless, there are still several restrictions that must be overcome. For instance, ontology queries must be performed using a linguistic label set with an specific granularity value. In environments where several people have to deal with the same ontology, this can be an inconvenient since the chosen representation does not have to be suitable for all of them. In this paper, multi-granular fuzzy linguistic modelling methods have been used in order to deal with heterogeneous information coming from different sources and to allow experts to choose the linguistic label set that better fits their needs.es_ES
dc.language.isoenges_ES
dc.publisher2016 IEEE International conference on systems, man, and cybernetics (SMC)es_ES
dc.relation.urihttps://ieeexplore.ieee.org/document/7844256es_ES
dc.rightsrestrictedAccesses_ES
dc.subjectgroup decision-markinges_ES
dc.subjectSemantic webes_ES
dc.subjectKnowledgees_ES
dc.subjectContextses_ES
dc.subjectWOS(2)es_ES
dc.subjectScopus(2)es_ES
dc.titleImproving queries and representing heterogeneous information in fuzzy ontologies using multi-granular fuzzy linguistic modelling methodses_ES
dc.typeconferenceObjectes_ES
reunir.tag~ARIes_ES
dc.identifier.doihttps://doi.org/10.1109/SMC.2016.7844256


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