DocumentCode
441779
Title
Novel measurement for mining effective association rules
Author
Wei, Jin-Mao ; Yi, Wei-Guo ; Wang, Ming-Yang
Author_Institution
Inst. of Computational Intelligence, Northeast Normal Univ., ChangChun, China
Volume
3
fYear
2005
fDate
18-21 Aug. 2005
Firstpage
1660
Abstract
In this paper, we analyze the method of support-confidence framework when mining association rules. In order to avoid the limitation in the criterion, we propose a new method of match as the substitution of confidence. We analyze in detail the property of the proposed measurement. Experimental results show that there is higher correlation between the antecedent and the consequent of the rules produced by the improved method compared with the rules produced by the support-confidence framework. Furthermore, the improved method decreases the generation of redundancy rules.
Keywords
data mining; association rules; data mining; support-confidence framework; Association rules; Computational intelligence; Data mining; Electronic mail; Frequency; Knowledge engineering; Laboratories; Merchandise; Neural networks; Transaction databases; Data mining; association rules; correlation; match;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location
Guangzhou, China
Print_ISBN
0-7803-9091-1
Type
conf
DOI
10.1109/ICMLC.2005.1527211
Filename
1527211
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