Aufsatz
Mining minimal non-redundant association rules using frequent closed itemsets
Abstract
The problem of the relevance and the usefulness of extracted association rules is of primary importance because, in the majority of cases, real-life databases lead to several thousands association rules with high confidence and among which are many redundancies. Using the closure of the Galois connection, we define two new bases for association rules which union is a generating set for all valid association rules with support and confidence. These bases are characterized using frequent closed itemsets and their generators; they consist of the non-redundant exact and approximate association rules having minimal antecedents and maximal consequences, i.e. the most relevant association rules. Algorithms for extracting these bases are presented and results of experiments carried out on real-life databases show that the proposed bases are useful, and that their generation is not time consuming.
Citation
@article{urn:nbn:de:hebis:34-2009022326389,
author={Bastide, Yves and Pasquier, Nicolas and Taouil, Rafik and Stumme, Gerd and Lakhal, Lotfi},
title={Mining minimal non-redundant association rules using frequent closed itemsets},
year={2000}
}
0500 Oax
0501 Text $btxt$2rdacontent
0502 Computermedien $bc$2rdacarrier
1100 2000$n2000
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2050 ##0##urn:nbn:de:hebis:34-2009022326389
3000 Bastide, Yves
3010 Pasquier, Nicolas
3010 Taouil, Rafik
3010 Stumme, Gerd
3010 Lakhal, Lotfi
4000 Mining minimal non-redundant association rules using frequent closed itemsets / Bastide, Yves
4030
4060 Online-Ressource
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5550 {{Data Mining}}
5550 {{Effizienter Algorithmus}}
7136 ##0##urn:nbn:de:hebis:34-2009022326389
<resource xsi:schemaLocation="http://datacite.org/schema/kernel-2.2 http://schema.datacite.org/meta/kernel-2.2/metadata.xsd"> 2009-02-23T15:50:07Z 2009-02-23T15:50:07Z 2000 urn:nbn:de:hebis:34-2009022326389 http://hdl.handle.net/123456789/2009022326389 253958 bytes application/pdf eng Urheberrechtlich geschützt https://rightsstatements.org/page/InC/1.0/ 004 Mining minimal non-redundant association rules using frequent closed itemsets Aufsatz The problem of the relevance and the usefulness of extracted association rules is of primary importance because, in the majority of cases, real-life databases lead to several thousands association rules with high confidence and among which are many redundancies. Using the closure of the Galois connection, we define two new bases for association rules which union is a generating set for all valid association rules with support and confidence. These bases are characterized using frequent closed itemsets and their generators; they consist of the non-redundant exact and approximate association rules having minimal antecedents and maximal consequences, i.e. the most relevant association rules. Algorithms for extracting these bases are presented and results of experiments carried out on real-life databases show that the proposed bases are useful, and that their generation is not time consuming. open access Bastide, Yves Pasquier, Nicolas Taouil, Rafik Stumme, Gerd Lakhal, Lotfi Extern Auch erschienen in: Lloyd, John u.a. (Hrsg.): Computationa logic. (Lecture notes in computer science ; 1861). Berlin u.a. : Springer, 2000. ISBN 3-540-67797-6. (The original publication is available at www.springerlink.com) Data Mining Effizienter Algorithmus </resource>
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