Title :
A General Framework for Fuzzy Data Mining
Author :
Zhao, Jitao ; Yao, Lin
Author_Institution :
Dept. of Educ. Technol. & Inf., Xuchang Univ., Xuchang, China
Abstract :
Mining association rules is one of the most important tasks in data mining. Several approaches generalizing association rules to fuzzy association rules have been proposed. In this paper we present a general framework for mining fuzzy association rule. Based on apriori algorithm, a new algorithm for mining fuzzy association rules is proposed. Experimental results illustrate the algorithm is more effective.
Keywords :
data mining; fuzzy set theory; relational databases; apriori algorithm; association rules; fuzzy association rules; fuzzy data mining; Association rules; Diseases; Helium; Itemsets; Web sites;
Conference_Titel :
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5391-7
Electronic_ISBN :
978-1-4244-5392-4
DOI :
10.1109/CISE.2010.5676960