Multi-objective genetic algorithm based method for mining optimized fuzzy association rules

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dc.contributor.authorKaya, M
dc.contributor.authorAlhajj, R
dc.date.accessioned2026-08-12T16:34:57Z
dc.date.issued2004
dc.departmentFırat Üniversitesi
dc.description5th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2004) -- AUG 25-27, 2004 -- Execter, ENGLAND
dc.description.abstractThis paper introduces optimized fuzzy association rules mining. We propose a multi-objective Genetic Algorithm (GA) based approach for mining fuzzy association rules containing instantiated and uninstantiated attributes. According to our method, fuzzy association rules can contain an arbitrary number of uninstantiated attributes. The method uses three objectives for the rule mining process: support, confidence and number of fuzzy sets. Experimental results conducted on a real data set demonstrate the effectiveness and applicability of the proposed approach.
dc.description.sponsorshipExecter Univ, Comp Sci Dept,IEEE Neural Networks Soc,Springer Verlag
dc.identifier.endpage764
dc.identifier.isbn3-540-22881-0
dc.identifier.issn0302-9743
dc.identifier.orcid0000-0003-2995-8282
dc.identifier.scopus2-s2.0-35048832463
dc.identifier.scopusqualityQ3
dc.identifier.startpage758
dc.identifier.urihttps://hdl.handle.net/11508/44678
dc.identifier.volume3177
dc.identifier.wosWOS:000223701300113
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer-Verlag Berlin
dc.relation.ispartofIntelligent Daa Engineering and Automated Learning Ideal 2004, Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.titleMulti-objective genetic algorithm based method for mining optimized fuzzy association rules
dc.typeConference Object

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