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dc.creatorAlcalde, Cristinaes_ES
dc.creatorBurusco Juandeaburre, Anaes_ES
dc.date.accessioned2020-01-27T09:50:37Z
dc.date.available2020-05-23T23:00:10Z
dc.date.issued2019
dc.identifier.issn0308-1079
dc.identifier.urihttps://hdl.handle.net/2454/36161
dc.description.abstractInformation extraction from an L-fuzzy context becomes a hard problem when we work with a large set of objects and/or attributes. The goal of this paper is to present two different and complementary techniques to reduce the size of the context. First, using overlap indexes, we will establish rankings among the elements of the context that will allow us to determine those that do not provide relevant information and eliminate them. Second, by means of Choquet integrals, we will aggregate some objects or attributes of the context in order to jointly use the provided information. One interesting application of the developed theory consists on helping in the differential diagnoses of diseases that share a large number of symptoms and, therefore, that are difficult of distinguish.en
dc.description.sponsorshipThis paper is partially supported by the Research Group 'Intelligent Systems and Energy (SI+E)' of the University of the Basque Country – UPV/EHU [grant number GIU 16/54] and by the Research Group 'Artificial Intelligence and Approximate Reasoning' of the Public University of Navarra [grant number TIN2016-77356-P].en
dc.format.extent22 p.
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherTaylor & Francisen
dc.relation.ispartofInternational Journal of General Systems, 2019, vol. 48, no. 7, 692-712en
dc.rights© 2019 Informa UK Limited, trading as Taylor & Francis Group.en
dc.subjectL-fuzzy contexten
dc.subjectL-fuzzy concepten
dc.subjectChoquet integralen
dc.subjectOverlap indexesen
dc.subjectDifferential diagnosisen
dc.titleReduction of the size of L-fuzzy contexts. A tool for differential diagnoses of diseasesen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeArtículo / Artikuluaes
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticases_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Sailaeu
dc.contributor.departmentUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa. ISC - Institute of Smart Citieses_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.embargo.terms2020-05-23
dc.identifier.doi10.1080/03081079.2019.1620740
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/TIN2016-77356-Pen
dc.relation.publisherversionhttps://doi.org/10.1080/03081079.2019.1620740
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.type.versionVersión aceptada / Onetsi den bertsioaes


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