AAAI Publications, Twenty-Third International FLAIRS Conference

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Optimized Mining of a Concise Representation for Frequent Patterns based on Disjunctions Rather than Conjunctions
Tarek Hamrouni, Sadok Ben Yahia, Engelbert Mephu Nguifo

Last modified: 2010-05-06


Exact condensed representations were introduced in order to offer a small-sized set of elements from which the faithful retrieval of all frequent patterns is possible. In this paper, a new exact concise representation only based on particular elements from the disjunctive search space will be introduced. In this space, a pattern is characterized by its disjunctive support, i.e., the frequency of complementary occurrences -- instead of the ubiquitous co-occurrence link -- of its items. In this respect, we mainly focus here on proposing an efficient tool for mining this representation. For this purpose, we introduce an algorithm, called DSSRM, dedicated to this task. We also propose several techniques to optimize its mining time and memory consumption. The empirical study carried out on benchmark datasets shows that DSSRM is faster by several orders of magnitude than MEP; the mining algorithm of the unique other representation using disjunctions of items.


Algorithm; Frequent pattern; Concise representation; Disjunctive support; Disjunctive closed pattern; Essential pattern

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