Study on efficient algorithm of frequent item-set mining

Abstract

To further improve the scalability of the algorithm for frequent item-set mining, studies on the frequent item-set search space and the FP-tree operation method were made. On this basis, an efficient algorithm for frequent item-set mining based on the a set of frequent-pattern list(FPL)is presented, which employs the strategy of incremental construction of a candidate itemset and Apriori property to reduce the searching space, and gets support-count of the frequent itemset by intersecting tid-list. Lastly the algorithm is realized on experiment and is proved to be valid.