%0
%0 Journal Article
%A Pasquier, Nicolas; Taouil, Rafik; Bastide, Yves; Stumme, Gerd & Lakhal, Lotfi
%D 2005
%T Generating a Condensed Representation for Association Rules
%E
%B Journal Intelligent Information Systems (JIIS)
%C
%I Kluwer Academic Publishers
%V 24
%6
%N 1
%P 29-60
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%F pasquier2005generating
%K concept, discovery, 2005, association, OntologyHandbook, l3s, analysis, kdd, itemset, myown, rule, data, knowledge, closed, formal, rules, itegpub, condensed, fca, sets, representations, mining
%X
%Z
%U http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf
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%0
%0 Journal Article
%A Pasquier, Nicolas; Taouil, Rafik; Bastide, Yves; Stumme, Gerd & Lakhal, Lotfi
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%T Generating a Condensed Representation for Association Rules
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%P 29-60
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%F pasquier2005generating
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%U http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf
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%0 Journal Article
%A Stumme, Gerd; Taouil, Rafik; Bastide, Yves; Pasquier, Nicolas & Lakhal, Lotfi
%D 2002
%T Computing iceberg concept lattices with TITANIC
%E
%B Data & Knowledge Engineering
%C
%I Elsevier Science Publishers B. V.
%V 42
%6
%N 2
%P 189--222
%&
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%7
%8 August
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%@ 0169-023X
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%F stumme2002computing
%K titanic, concept, iceberg, fca, kdd, computing
%X We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association rules. Iceberg concept lattices are based on the theory of Formal Concept Analysis, a mathematical theory with applications in data analysis, information retrieval, and knowledge discovery. We present a new algorithm called TITANIC for computing (iceberg) concept lattices. It is based on data mining techniques with a level-wise approach. In fact, TITANIC can be used for a more general problem: Computing arbitrary closure systems when the closure operator comes along with a so-called weight function. The use of weight functions for computing closure systems has not been discussed in the literature up to now. Applications providing such a weight function include association rule mining, functional dependencies in databases, conceptual clustering, and ontology engineering. The algorithm is experimentally evaluated and compared with Ganter's Next-Closure algorithm. The evaluation shows an important gain in efficiency, especially for weakly correlated data.
%Z
%U http://portal.acm.org/citation.cfm?id=606457
%+
%^
%0
%0 Journal Article
%A Stumme, Gerd; Taouil, Rafik; Bastide, Yves; Pasquier, Nicolas & Lakhal, Lotfi
%D 2002
%T Computing iceberg concept lattices with TITANIC
%E
%B Data \& Knowledge Engineering
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%I Elsevier Science Publishers B. V.
%V 42
%6
%N 2
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%X We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association rules. Iceberg concept lattices are based on the theory of Formal Concept Analysis, a mathematical theory with applications in data analysis, information retrieval, and knowledge discovery. We present a new algorithm called TITANIC for computing (iceberg) concept lattices. It is based on data mining techniques with a level-wise approach. In fact, TITANIC can be used for a more general problem: Computing arbitrary closure systems when the closure operator comes along with a so-called weight function. The use of weight functions for computing closure systems has not been discussed in the literature up to now. Applications providing such a weight function include association rule mining, functional dependencies in databases, conceptual clustering, and ontology engineering. The algorithm is experimentally evaluated and compared with Ganter's Next-Closure algorithm. The evaluation shows an important gain in efficiency, especially for weakly correlated data.
%Z
%U http://portal.acm.org/citation.cfm?id=606457
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%0
%0 Conference Proceedings
%A Pasquier, Nicolas; Bastide, Yves; Taouil, Rafik & Lakhal, Lotfi
%D 1998
%T Pruning closed itemset lattices for associations rules.
%E Bouzeghoub, Mokrane
%B Bases de Donn�es Avanc�es
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%3 inproceedings
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%F pasquier98pruning
%K rules, closed, concept, formal, association, OntologyHandbook, FCA, analysis, fca, itemset, mining
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%U http://dblp.uni-trier.de/db/conf/bda/bda98.html#PasquierBTL98
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%0
%0 Conference Proceedings
%A Pasquier, Nicolas; Bastide, Yves; Taouil, Rafik & Lakhal, Lotfi
%D 1998
%T Pruning closed itemset lattices for associations rules.
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%B Bases de Données Avancées
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%U http://dblp.uni-trier.de/db/conf/bda/bda98.html#PasquierBTL98
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