Mining positive and negative association rules

	Mining positive and negative association rules
	Zhu, Honglei; Xu, Zhigang
	2008
关键词	Correlation methods Data mining Correlation coefficient Effectiveness and efficiencies Frequent itemset Minimum support thresholds Mining methods Negative association rules Pruning Pruning strategy
卷号	3
页码	2748-2752
英文摘要	Recently, mining negative association rules has received some attention and been proved to be useful in real world. This paper presents an efficient algorithm(PNAR) for mining both positive and negative association rules in databases. The algorithm extends traditional association rules to include negative association rules. When mining negative association rules, we adopt another minimum support threshold to mine frequent negative itemsets. With a correlation coefficient measure and pruning strategies, the algorithm can find all valid association rules quickly and overcome some limitations of the previous mining methods. The experimental results demonstrate its effectiveness and efficiency. Copyright©(2008) by Computers & Industrial Engineering.
会议录	38th International Conference on Computers and Industrial Engineering 2008
会议录出版者	Computers and Industrial Engineering
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116843]
专题	计算机与通信学院
作者单位	School of Computer and Communication, Lanzhou University of Technology GS, China
推荐引用方式 GB/T 7714	Zhu, Honglei,Xu, Zhigang. Mining positive and negative association rules[C]. 见:.