An improved association rule algorithm based on Itemset Matrix and Cluster Matrix
Peng Jian, Xiaoling Wang · 2012
Through the analysis of the method of association rules, an improved algorithm in association rules based on Itemset Matrix(ISM) and Cluster Matrix(CMa) is put forward. The algorithm can get the new frequent itemsets just through scanning the updated data once again, when the database and the minimum support degree are changed. Studies and analysis of the algorithm show that it just need to scan the database once, so it has the virtues in high-speed producing frequent k-itemsets and less time cost. And it improves the efficiency of the association mining, can fulfill the request of shortening the time of mining.