Research on Mining Positive and Negative Association Rules

摘要：

Positive and negative association rules are important to find useful information hided in massive data sets, especially negative association rules can reflect mutually exclusive correlaiton among items. Despite a great deal of research, a number of challenges still exist in mining positive and negative association rules. In order to solve the problem of difficult to determine frequent item sets and how to delete contradictive positive and negative association rules, the paper presents a new algorithm for mining positive and negative association rules. The algorithm applies a new measurement framework of support and confidence to solve the problems existing. The performance study shows that the method is highly efficient and accurate in comparison with other reported mining methods.

关键词： Association Rules Data Mining Negative Association Rules Positive Association Rules

作者: LUO Junwei Zhang Bo

作者单位: College of Computer Science and Technology Henan Polytechnic University JiaoZuo, Henan Province Chin School of Mathematics and Information Science Henan Polytechnic University JiaoZuo, Henan Province C

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

会议地点: 成都

会议语种:英文

页码: 302-304

在线出版日期: 2010-06-12（万方平台首次上网日期，不代表论文的发表时间）