A novel incremental updating algorithm for maintaining discovered negative association rules

doi:10.1109/ICRCCS.2009.49

	A novel incremental updating algorithm for maintaining discovered negative association rules
	Zhu, Honglei; Z., Xu
	2009
会议日期	December 28, 2009 - December 29, 2009
会议地点	Shanghai, China
关键词	Association rules Correlation coefficient Data mining problems Effectiveness and efficiencies Incremental updates Incremental updating Itemset Negative association rules Pruning strategy
DOI	10.1109/ICRCCS.2009.49
页码	164-167
英文摘要	Recently, mining negative association rules is an important research topic among various data mining problems and has been proved to be useful in real world. The issue of maintaining discovered negative association rules is paid more attention in the same way. Especially, the process of updating frequent negative itemsets is still a complicated issue for dynamic database that involve frequent additions. This paper presents an efficient algorithm INAR for mining negative association rules in incremental updating databases. With a correlation coefficient measure and pruning strategies, the INAR algorithm can find all valid negative association rules quickly and overcome some limitations of the previous mining methods. The experimental results demonstrate its effectiveness and efficiency. © 2009 IEEE.
会议录	ICRCCS 2009 - 2009 International Conference on Research Challenges in Computer Science
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/116366]
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,Z., Xu. A novel incremental updating algorithm for maintaining discovered negative association rules[C]. 见:. Shanghai, China. December 28, 2009 - December 29, 2009.