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Mining quantitative association rules on overlapped intervals
Tong, Q; Yan, BP; Zhou, YC
2005
发表期刊ADVANCED DATA MINING AND APPLICATIONS, PROCEEDINGS
ISSN0302-9743
卷号3584页码:43-50
摘要Mining association rules is an important problem in data mining. Algorithms for mining boolean data have been well studied and documented, but they cannot deal with quantitative and categorical data directly. For quantitative attributes, the general idea is partitioning the domain of a quantitative attribute into intervals, and applying boolean algorithms to the intervals. But, there is a conflict between the minimum support problem and the minimum confidence problem, while existing partitioning methods cannot avoid the conflict. Moreover, we expect the intervals to be meaningful. Clustering in data mining is a discovery process which groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. The discovered clusters are used to explain the characteristics of the data distribution. The present paper will propose a novel method to find quantitative association rules by clustering the transactions of a database into clusters and projecting the clusters into the domains of the quantitative attributes to form meaningful intervals which may be overlapped. Experimental results show that our approach can efficiently find quantitative association rules, and can find important association rules which may be missed by the previous algorithms.
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS记录号WOS:000230895000007
出版者SPRINGER-VERLAG BERLIN
引用统计
被引频次:16[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/10018
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Tong, Q
作者单位1.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
2.Chinese Acad Sci, Comp Network Informat Ctr, Beijing, Peoples R China
3.Chinese Acad Sci, Grad Sch, Beijing, Peoples R China
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Tong, Q,Yan, BP,Zhou, YC. Mining quantitative association rules on overlapped intervals[J]. ADVANCED DATA MINING AND APPLICATIONS, PROCEEDINGS,2005,3584:43-50.
APA Tong, Q,Yan, BP,&Zhou, YC.(2005).Mining quantitative association rules on overlapped intervals.ADVANCED DATA MINING AND APPLICATIONS, PROCEEDINGS,3584,43-50.
MLA Tong, Q,et al."Mining quantitative association rules on overlapped intervals".ADVANCED DATA MINING AND APPLICATIONS, PROCEEDINGS 3584(2005):43-50.
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