Mining Frequent and Homogeneous Closed Itemsets

Inès Hilali, Tao-Yuan Jen, Dominique Laurent, Claudia Marinica, Sadok Ben Yahia

Abstract: It is well known that when mining frequent itemsets from a transaction database, the output is usually too large to be effectively exploited by users. To cope with this difficulty, several forms of condensed representations of the set of frequent itemsets have been proposed, among which the notion of closure is one of the most popular. In this paper, we propose a new notion of closure that takes into account, not only the support of itemsets, but also their homogeneity degree with respect to a given taxonomy. To this end, we introduce and study the notion of frequent and homogeneous closed itemset and we show in particular that knowing all frequent and homogeneous closed itemsets along with their supports and homogeneity degrees, allows to know all frequent and homogenous itemsets. Moreover, we propose a level wise algorithm for mining frequent and homogeneous closed itemsets.