Title :
A fuzzy weight algorithm for mining infrequent association rules
Author :
Zhengxin, Li ; Fengming, Zhang ; Xiaodong, Lin ; Kewu, Li
Author_Institution :
Eng. Inst., Air Force Eng. Univ. AFEU, Xi´´an, China
Abstract :
The paper introduces the conception of significance and presents a new algorithm -a fuzzy weight algorithm with multiple supports for mining association rules, which is based on fuzzy-comprehensive evaluation and the algorithm of multiple minimum supports. The new algorithm takes support and significance into consideration at the same time when large itemsets are produced, making the filter criterion more reasonable and not missing items with high significance but low supports.
Keywords :
data mining; fuzzy set theory; data mining; filter criterion; fuzzy weight algorithm; mining association rules; Association rules; Data mining; Electronic mail; Filters; Itemsets; Transaction databases; association rules; data mining; fuzzy-comprehensive evaluation; weight algorithm with multiple supports;
Conference_Titel :
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5263-7
Electronic_ISBN :
978-1-4244-5265-1
DOI :
10.1109/ICIME.2010.5477565
