Intelligent structuring and reducing of association rules with formal concept analysis

dc.date.accessioned	2009-02-27T14:49:18Z
dc.date.available	2009-02-27T14:49:18Z
dc.date.issued	2001
dc.identifier.uri	urn:nbn:de:hebis:34-2009022726493
dc.identifier.uri	http://hdl.handle.net/123456789/2009022726493
dc.format.extent	335363 bytes
dc.format.mimetype	application/pdf
dc.language.iso	eng
dc.rights	Urheberrechtlich geschützt
dc.rights.uri	https://rightsstatements.org/page/InC/1.0/
dc.subject.ddc	004
dc.title	Intelligent structuring and reducing of association rules with formal concept analysis	eng
dc.type	Preprint
dcterms.abstract	Association 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.accessRights	open access
dcterms.creator	Stumme, Gerd
dcterms.creator	Taouil, Rafik
dcterms.creator	Bastide, Yves
dcterms.creator	Pasquier, Nicolas
dcterms.creator	Lakhal, Lotfi
dc.description.et	Extern	ger
dc.description.everything	Auch 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.swd	Formale Begriffsanalyse	ger