DocumentCode
2337489
Title
A new algorithm for mining fuzzy association rules
Author
Gao, Ya ; Ma, Jun ; Ma, Lin
Author_Institution
Sch. of Comput. & Commun. Eng., Southwest Jiaotong Univ., Sichuan, China
Volume
3
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
1635
Abstract
We introduce a new algorithm for mining the fuzzy association rules by removing redundant fuzzy association (RFA) rules. Firstly, we analyze some properties of fuzzy association rules and give the definition of RFA rules. Secondly, using the degree of implication on fuzzy implication operator, we introduce a new algorithm to mine fuzzy association rules from frequent itemsets. Finally, an example is given to illustrate our idea.
Keywords
data mining; fuzzy set theory; mathematical operators; fuzzy association rule mining; fuzzy implication operator; redundant fuzzy association; Association rules; Data mining; Electronic mail; Fuzzy sets; Itemsets; Large-scale systems; Measurement standards; Partitioning algorithms; Pharmaceuticals; Transaction databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382037
Filename
1382037
Link To Document