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dc.date.accessioned2009-03-17T08:25:43Z
dc.date.available2009-03-17T08:25:43Z
dc.date.issued2004
dc.identifier.uriurn:nbn:de:hebis:34-2009031726692
dc.identifier.urihttp://hdl.handle.net/123456789/2009031726692
dc.format.extent153240 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.subject.ddc004
dc.titleIceberg query lattices for datalogeng
dc.typePreprint
dcterms.abstractIn this paper we study two orthogonal extensions of the classical data mining problem of mining association rules, and show how they naturally interact. The first is the extension from a propositional representation to datalog, and the second is the condensed representation of frequent itemsets by means of Formal Concept Analysis (FCA). We combine the notion of frequent datalog queries with iceberg concept lattices (also called closed itemsets) of FCA and introduce two kinds of iceberg query lattices as condensed representations of frequent datalog queries. We demonstrate that iceberg query lattices provide a natural way to visualize relational association rules in a non-redundant way.eng
dcterms.accessRightsopen access
dcterms.creatorStumme, Gerd
dc.description.everythingAuch erschienen in: Wolff, Karl Erich u.a. (Hrsg.): Conceptual structures at work. (Lecture notes in computer science ; 3127). Berlin u.a. : Springer, 2004. S. 109-125. ISBN 3-540-22392-4 (The original publication is available at www.springerlink.com)ger
dc.subject.swdData Miningger
dc.subject.swdFormale Begriffsanalyseger


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