Fuzzy correlation rules mining

Authors:
Nancy P. Lin;Hao-En Chueh
Affiliations:
Department of Computer Science and Information Engineering, Tamkang University, Tamsui, Taipei, Taiwan;Department of Computer Science and Information Engineering, Tamkang University, Tamsui, Taipei, Taiwan
Venue:
ACOS'07 Proceedings of the 6th Conference on WSEAS International Conference on Applied Computer Science - Volume 6
Year:
2007

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Abstract

General fuzzy association rules mining focuses on finding out the fuzzy itemsets or fuzzy attributes which frequently occur together. But two fuzzy itemsets which frequently occur together can not imply that there is always an interesting relationship between them. In this paper, we develop an alternative framework for mining interesting relationship between fuzzy itemsets based on fuzzy correlation analysis, and the discovered rules are called fuzzy correlation rules. The analysis of fuzzy correlation can show us the strength and the type of the linear relationship between two fuzzy itemsets, and hence can prevent generating the misleading rules.