Association Rules Optimization Algorithm Based on Fuzzy Clustering

Yu Fu; Jun Rui Yang

doi:10.4028/www.scientific.net/AMM.602-605.3536

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Association Rules Optimization Algorithm Based on...

Association Rules Optimization Algorithm Based on Fuzzy Clustering

Abstract:

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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Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

3536-3539

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.3536

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Online since:

August 2014

Authors:

Yu Fu*, Jun Rui Yang

Keywords:

Data Preprocessing, Fuzzy Clustering, Fuzzy FP_Tree

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