Association rules optimization algorithm based on fuzzy clustering

Yu Fu; JunRui Yang
August 2014
Applied Mechanics & Materials;2014, Issue 602-605, p3536
Academic Journal
Frequent pattern mining has been an important research direction in association rules. This paper use a methodology by preprocessing the original dataset using fuzzy clustering which can mapped quantitative datasets into linguistic datasets. Then we propose a algorithm based on fuzzy frequent pattern tree for extracting fuzzy frequent itemset from mapped linguistic datasets. Experimental results show that our algorithm is shorter than the F-Apriori on computing time to huge database. For large database, the algorithm presented in this paper is proved to have a good prospect.


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