Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (3): 139-141.DOI: 10.3778/j.issn.1002-8331.2011.03.042

• 数据库、信号与信息处理 • Previous Articles     Next Articles

Research on high efficiency mining frequent itemsets on association rules

ZHANG Yuntao1,YU Zhilou2,ZHANG Huaxiang1   

  1. 1.School of Information Science and Engineering,Shandong Normal University,Jinan 250014,China
    2.Inspur Group,Jinan 250101,China
  • Received:2009-06-26 Revised:2009-10-23 Online:2011-01-21 Published:2011-01-21
  • Contact: ZHANG Yuntao



  1. 1.山东师范大学 信息科学与工程学院,济南 250014
    2.浪潮集团有限公司,济南 250101
  • 通讯作者: 张云涛

Abstract: An improved algorithm Apriori-M which combines with 2-itemsets support count matrix is brought forward for its lower efficiency of time.The algorithm scans the database to generate 2-itemsets support count matrix,and then improves the efficiency of the connectivity and the pruning by the character of the matrix;gets all the frequent itemsets correctly by scanning the database second time,and also solves the question about generating 2-itemsets invalid.Experimental results show that the capability of the improved algorithm is more efficient than Apriori.

Key words: association rules, Apriori algorithm, transaction database, frequent itemsets, support matrix

摘要: 针对Apriori时间性能较低的缺陷,结合二项集支持度矩阵提出了Apriori改进算法Apriori-M。在扫描数据库时生成一个二项集支持度矩阵,利用矩阵的性质提高了连接和剪枝的效率;通过第二次扫描数据库就能正确地获取所有的频繁项集,并很好地解决了Apriori生成无效二项集的问题。实验结果表明Apriori-M的性能优于Apriori。

关键词: 关联规则, Apriori算法, 事务数据库, 频繁项, 支持度矩阵

CLC Number: