CROSS CORRELATION BASED INTER-TRANSACTION ASSOCIATION RULE MINING TECHNIQUE

Several algorithms have been proposed to solve the problem of mining frequent inter-transaction itemset. However, the low efficiency of support calculation for inter-transaction itemsets is still a challenging problem that eliminates the performance of mining algorithms. This paper provides intertransaction association rule mining algorithm using effective technique for support calculations. The proposed technique is based on cross correlation and bitwise operations. The experimental results show a significant improvement of performance up to several orders of magnitude compared to First Intra Then Inter (FITI) algorithm.