An algorithm of improved association rules mining

In this paper, in order to reduce the times of scanning database when presented algorithms compute support of candidate frequent itemsets, in order to improve the method of computing support of candidate frequent itemsets, and in order to further improve the efficiency of algorithm, based on up search strategy of Apriori, we propose an algorithm of association rules mining based on sequence number. The algorithm would use the method of binary Boolean calculation to generate candidate frequent itemsets of binary form, and gain support of candidate frequent itemsets by computing Sequence Number Degree (SND), which is gained through computing these Sequence Number (SN) of all these items contained by candidate frequent itemsets. The algorithm only need scan once all these transactions in database to indeed improve the efficiency of algorithm. The experiment indicates the efficiency of this algorithm is faster and more efficient than presented algorithms.