Mining Association and Correlation Patterns Simultaneously in Database

摘要：

Data mining aims to discover useful patterns (rules) in large datasets. In order to enhance the interestingness of the patterns produced, we propose an algorithm to mine both association and correlation patterns among items. In the mining process the all-confidence and correlation-confidence measures are adopted simultaneously. The effectiveness of the proposed approach is demonstrated with the experiment results on some real data sets.

关键词： association rule correlation pattern database correlation-confidence data mining

作者: Jianlin Zhang Wensheng Zou

作者单位: School of Software Nanchang Univeristy Nanchang, 330047, PR China Institute of Computer Technology Engineering Nanchang Univeristy Nanchang, 330029, PR China

会议类型: 国际会议

会议名称: 2009 WASE International Conference on Information Engineering(2009年国际信息工程会议)(ICIE 2009)

会议地点: 太原

会议语种:英文

页码: 526-529

在线出版日期: 2009-07-10（万方平台首次上网日期，不代表论文的发表时间）