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Efficient Vertical Mining of Minimal Rare Itemsets

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 important sort of patterns that have a wide range of practical applications, in particular, in analysis of biomedical data. 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 that traverses the search space bottom up and proceeds in two steps: (1) moving across the frequent zone until the minimal rare itemsets are reached and (2) listing all rare itemsets. As the efficiency of the frequent zone traversal is crucial for the overall performance of the rare miner, we are looking for ways to speed it up. 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. The new method relies on a set of structural results that helps save a certain amount of computation and eventually ensures it outperforms the current levelwise procedure.
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Conference papers
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Submitted on : Thursday, December 27, 2012 - 4:06:18 PM
Last modification on : Friday, August 5, 2022 - 2:30:05 PM


  • HAL Id : hal-00769031, version 1


Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin. Efficient Vertical Mining of Minimal Rare Itemsets. CLA - The Ninth International Conference on Concept Lattices and Their Applications - 2012, 2012, Fuengirola, Spain. ⟨hal-00769031⟩



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