Finding minimal rare itemsets in a depth-first manner

Laszlo Szathmary 1 Petko Valtchev 2 Amedeo Napoli 3 Robert Godin 2
3 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Rare itemsets are an important sort of patterns that have a wide range of practical applications. Although mining rare patterns poses specific algorithmic problems, it is yet insufficiently studied. In a previous work, we proposed a levelwise approach for rare itemset mining. Here, we examine the benefits of depth-first methods for that task as such methods are known to outperform the levelwise ones in many practical cases.
Type de document :
Communication dans un congrès
Sergei O. Kuznetsov and Amedeo Napoli and Sebastian Rudolph. ECAI Workshop on Formal Concept Analysis for Artificial Intelligence (FCA4AI), Montpellier, 2012, Montpellier, France. CEUR Proceedings, 939, pp.71-78, 2012, ECAI Workshop on Formal Concept Analysis for Artificial Intelligence (FCA4AI), Montpellier
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https://hal.inria.fr/hal-00769028
Contributeur : Amedeo Napoli <>
Soumis le : jeudi 27 décembre 2012 - 15:58:26
Dernière modification le : jeudi 11 janvier 2018 - 06:25:24

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  • HAL Id : hal-00769028, version 1

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Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin. Finding minimal rare itemsets in a depth-first manner. Sergei O. Kuznetsov and Amedeo Napoli and Sebastian Rudolph. ECAI Workshop on Formal Concept Analysis for Artificial Intelligence (FCA4AI), Montpellier, 2012, Montpellier, France. CEUR Proceedings, 939, pp.71-78, 2012, ECAI Workshop on Formal Concept Analysis for Artificial Intelligence (FCA4AI), Montpellier. 〈hal-00769028〉

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