k-Frequent itemsets generation algorithm based on bit matrix

The generation of frequent itemsets is the key of association rules mining. Based on bit vectors and its intersection operation of the DLG ideas, this paper presents a new k-frequent itemsets generation algorithm based on bit matrix. The algorithm scans the database only once, using bit matrix of alternative association graph to store, constructing screening conditions to reduce the validation of candidate frequent itemsets in long patterns of frequent itemsets generated effectively. Compared with DLG, experimental results show the effectiveness and accuracy of this algorithm.