An Improved Apriori-based Algorithm for Association Rules Mining
Huan Wu, Zhigang Lü, Lin Pan, XU Rong-sheng, Wenbao Jiang · 2009
Because of the rapid growth in worldwide information, efficiency of association rules mining (ARM) has been concerned for several years. In this paper, based on the original Apriori algorithm, an improved algorithm IAA is proposed. IAA adopts a new count-based method to prune candidate itemsets and uses generation record to reduce total data scan amount. Experiments demonstrate that our algorithm outperforms the original Apriori and some other existing ARM methods.