Extending FuzAtAnalyzer to approach the management of classical negation

dc.centroEscuela Politécnica Superiores_ES
dc.contributor.authorRodríguez-Jiménez, J.M.
dc.contributor.authorCordero-Ortega, Pablo
dc.contributor.authorEnciso-García-Oliveros, Manuel
dc.contributor.authorMora-Bonilla, Ángel
dc.date.accessioned2015-09-16T10:01:48Z
dc.date.available2015-09-16T10:01:48Z
dc.date.created2015
dc.date.issued2015-09-16
dc.departamentoMatemática Aplicada
dc.description.abstractFuzAtAnalyzer was conceived as a Java framework which goes beyond of classical tools in formal concept analysis. Specifically, it successfully incorporated the management of uncertainty by means of methods and tools from the area of fuzzy formal concept analysis. One limitation of formal concept analysis is that they only consider the presence of properties in the objects (positive attributes) as much in fuzzy as in crisp case. In this paper, a first step in the incorporation of negations is presented. Our aim is the treatment of the absence of properties (negative attributes). Specifically, we extend the framework by including specific tools for mining knowledge combining crisp positive and negative attributes.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.es_ES
dc.identifier.orcidhttp://orcid.org/0000-0003-4548-8030es_ES
dc.identifier.urihttp://hdl.handle.net/10630/10264
dc.language.isoenges_ES
dc.relation.eventdate6/7/2015es_ES
dc.relation.eventplaceRota - Cádiz - Españaes_ES
dc.relation.eventtitleCMMSE 2015es_ES
dc.rightsby-nc-nd
dc.rights.accessRightsopen accesses_ES
dc.subjectAlgoritmoses_ES
dc.subject.otherFormal concept analysises_ES
dc.subject.otherAlgorithmses_ES
dc.subject.otherNegative attributeses_ES
dc.subject.otherImplicationses_ES
dc.titleExtending FuzAtAnalyzer to approach the management of classical negationes_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
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relation.isAuthorOfPublicationd9a4128d-07d3-4140-a0f8-b1942366cac0
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relation.isAuthorOfPublication.latestForDiscoveryfa6843d6-9749-4852-96b3-b43ee5378c6e

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