A New Algorithm for Mining Frequent Itemsets Based on Fp-Search Algorithm with K Road Pruning

Association rule mining is an important approach in data mining. Based on analyzing many previous algorithms such as Apriori, Fp-growth, Eclat and Fp-search, we propose a new algorithm named FPNMP-search to mine frequent itemsets. With no need to construct the MP-tree, FPNMP-Search algorithm can effectively prune the redundant path and mine all frequent itemsets. The experimental results show that FPNMPsearch is more efficient than Fp-growth and Fp-search.