摘要
挖掘关联规则是数据挖掘中一个重要的课题,产生频繁项集是其中的一个关键步骤。文章提出了一种基于矩阵压缩的Apriori优化算法,并将该算法与Apriori算法进行了比较。实验表明与Apriori算法相比,新算法的效率较好。
Mining association rules is an important problem in data mining,and Generating large itemsets is its key.This paper presents a novel algorithm based on Reducing matrix for Apriori, and compares it with Apriori algorithms. Experiment results indicate that the new algorithm has good efficiency compared with presented one.
出处
《微计算机信息》
2009年第12期213-215,共3页
Control & Automation
基金
国家自然科学资金资助项目(60472014)
