A condensed representation to find frequent patterns

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Abstract
Given a large set of data, a common data mining problem is to extract the frequent patterns occurring in this set. The idea presented in this paper is to extract a condensed representation of the frequent patterns called disjunction-free sets, instead of extracting the whole frequent pattern collection. We show that this condensed representation can be used to regenerate all frequent patterns and their exact frequencies. Moreover, this regeneration can be performed without any access to the original data. Practical experiments show that this representation can be extracted very efficiently even in difficult cases. We compared it with another representation of frequent patterns previously investigated in the literature called frequent closed sets. In nearly all experiments we have run, the disjunction-free sets have been extracted much more efficiently than frequent closed sets.

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