An effective algorithm for mining positive and negative association rules

doi:10.1109/CSSE.2008.1199

	An effective algorithm for mining positive and negative association rules
	Honglei, Zhu; Zhigang, Xu
	2008
会议日期	December 12, 2008 - December 14, 2008
会议地点	Wuhan, Hubei, China
关键词	Data mining Software engineering Correlation coefficient Effective algorithms Effectiveness and efficiencies Frequent itemset Minimum support thresholds Mining methods Negative association rules Pruning strategy
卷号	4
DOI	10.1109/CSSE.2008.1199
页码	455-458
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. © 2008 IEEE.
会议录	Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116849]
专题	计算机与通信学院
作者单位	School of Computer and Communication, Lanzhou University of Technology, LUT, GS, China
推荐引用方式 GB/T 7714	Honglei, Zhu,Zhigang, Xu. An effective algorithm for mining positive and negative association rules[C]. 见:. Wuhan, Hubei, China. December 12, 2008 - December 14, 2008.