A Novel Mining Method of Global Negative Association Rules in Multi-Database

摘要：

Mining Negative Association Rules in multi-database has attracted more and more attention. Most existing research focuses on unifying all negative rules discovered from different single databases into a single view. This paper presents a novel method for mining global negative association rules in multidatabase. This method produces some infrequent itemsets of potential interest by scanning constructed Multi-Database Frequent Pattern tree, and extracts negative association rules of interest according to the proposed correlation model from multi-database. Experimental results show the effectiveness and efficiency of the proposed algorithm.

关键词： multi-database mining association rules global negative associations

作者: Hong Li Yijun Shen Xuegang Hu

作者单位: Key Laboratory of Network and Intelligent Information Processing,Department of Computer Science and School of Computer & Information,Hefei University of technology,Hefei,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 392-396

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）