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.
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Conference papers
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https://hal.inria.fr/hal-00769028
Contributor : Amedeo Napoli <>
Submitted on : Thursday, December 27, 2012 - 3:58:26 PM
Last modification on : Wednesday, August 14, 2019 - 3:10:21 PM

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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. ECAI Workshop on Formal Concept Analysis for Artificial Intelligence (FCA4AI), Montpellier, 2012, Montpellier, France. pp.71-78. ⟨hal-00769028⟩

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