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dc.date.accessioned2009-02-27T14:49:18Z
dc.date.available2009-02-27T14:49:18Z
dc.date.issued2001
dc.identifier.uriurn:nbn:de:hebis:34-2009022726493
dc.identifier.urihttp://hdl.handle.net/123456789/2009022726493
dc.format.extent335363 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.subject.ddc004
dc.titleIntelligent structuring and reducing of association rules with formal concept analysiseng
dc.typePreprint
dcterms.abstractAssociation rules are used to investigate large databases. The analyst is usually confronted with large lists of such rules and has to find the most relevant ones for his purpose. Based on results about knowledge representation within the theoretical framework of Formal Concept Analysis, we present relatively small bases for association rules from which all rules can be deduced. We also provide algorithms for their calculation.eng
dcterms.accessRightsopen access
dcterms.creatorStumme, Gerd
dcterms.creatorTaouil, Rafik
dcterms.creatorBastide, Yves
dcterms.creatorPasquier, Nicolas
dcterms.creatorLakhal, Lotfi
dc.description.etExternger
dc.description.everythingAuch erschienen in: Baader, Franz u.a. (Hrsg.): Advances in artificial intelligence. (Lecture notes in computer science ; 2174). Berlin u.a. : Springer, 2001. S. 335-350. ISBN 3-540-42612-4 (The original publication is available at www.springerlink.com)ger
dc.subject.swdFormale Begriffsanalyseger


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