Research on Mining Sequential Positive and Negative Association Rules

摘要：

Mining sequential positive and negative association rules is to mine the inner association or the causal relationship among data in sequential database, which will find some rules that have practical significance for the industry decision making analysis among the sequence. This paper proposes the relational notions of sequential positive and negative association rule. Based on the new questions when mining the positive and negative rules in the sequential database, the paper discusses the solutions and proposes an algorithm called SPNARM to mine sequential positive and negative association rules (SPNAR). Example analysis results show that SPNARM algorithm is more efficient for mining SPNARs.

关键词： Sequential Pattern Negative Association Rule Infrequent Sequence Sequential Positive and Negative Association Rule

作者: He Jiang Runian Geng Baoyou Sun

作者单位: School of Information Science and Technology Shandong Institute of Light Industry Jinan, China

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 2629-2632

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