Abstract: In the frectuent itemsets mining, many algorithms are based on Apriori. These algorithms have two common problems. First,a lot of memory space are occupied by the entire database which must be loaded. Second,The processes of generating candidate itemset and computing support spend a lot of time. In order to improve efficiency, a BitTablc based form mining frequent itemsets algorithm Hash-BFI was proposed. The database was compressed into the BitTable in accordance with horizontal and vertical direction saving lots of place, used the hash function to compute the frequent two itemsets,also completely utilized AND,OR operation to generate candidate itemset and compute support for candidate itemset,and producted a pruning. All these meatures improve the efficiency of algorithm.

Key words: Apriori, Frequent itemsets, BitTable, Hash