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
Link To Document :
بازگشت