Mining Positive and Negative Association Rules in Multi-database Based on Minimum Interestingness

摘要：

With the increasing development and application of information and communication technologies, multi database mining is becoming more and more important. Association rules mining is the major topic in multi-database. According to Piatetsky-Shapiros argument, an association rule is interesting only if the rule meets the minimum interestingness condition. In this paper, we extended this condition to mine association rules in multi-database and improved it to check the correlation of association rules. An algorithm PNAR_MDB_on P-S measure is proposed and the experimental results demonstrated the algorithm is effective.

作者: Shi-ju SHANG Xiang-jun DONG Jie LI Yuan-yuan ZHAO

作者单位: Shandong Institute of Light Industry, School of Information Science and Technology, Shandong Jinan 2 Shandong Institute of Light Industry, School of Information Science and Technology, Shandong Jinan 2 College of Mathematics and Information Science, Guangxi University, Guangxi, Nanning 530004

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 791-794

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）