A Two-Way Hybrid Algorithm for Maximal Frequent Itemsets Mining

Abstract

A new two-way-hybrid algorithm for mining maximal frequent itemsets is proposed. A flexible two-way-hybrid search method is given. The two-way-hybrid search begins the mining procedure in both the top-down and bottom-up directions at the same time. Moreover, information gathered in the bottom-up can be used to prune the search space in the other top-down direction. Some efficient decomposition and pruning strategies are implied in this method, which can reduce the original search space rapidly in the iterations. Experimental and analytical results are presented in the end.