Abstrakt

USING HASH BASED APRIORI ALGORITHM TO REDUCE THE CANDIDATE 2- ITEMSETS FOR MINING ASSOCIATION RULE

K.Vanitha and R.Santhi

In this paper we describe an implementation of Hash based Apriori. We analyze, theoretically and experimentally, the principal data structure of our solution. This data structure is the main factor in the efficiency of our implementation. We propose an effective hash-based algorithm for the candidate set generation. Explicitly, the number of candidate 2-itemsets generated by the proposed algorithm is, in orders of magnitude, smaller than that by previous methods, thus resolving the performance bottleneck. Our approach scans the database once utilizing an enhanced version of priori algorithm.Note that the generation of smaller candidate sets enables us to effectively trim the transaction database size at a much earlier stage of the iterations, thereby reducing the computational cost for later iterations significantly