Enhance the Multi-level Fuzzy Association Rules Based on Cumulative Probability Distribution Approach

Author

Chen, Jr-Shian ; Wang, Jen-Ya ; Chen, Fuh-Gwo

Author_Institution

Dept. of Comput. Sci. & Inf. Manage., Hungkuang Univ., Taichung, Taiwan

fYear

2012

fDate

8-10 Aug. 2012

Firstpage

89

Lastpage

94

Abstract

This paper introduces a fusion model to reinforce multi-level fuzzy association rules, which integrated cumulative probability distribution approach (CPDA) and multi-level taxonomy concepts to extract fuzzy association rules. The proposed model generate large item sets level by level and mine multi-level fuzzy association rule lead to finding more informative and important knowledge from transaction dataset, which is more objective and reasonable in determining the universe of discourse and membership functions with other multi-level fuzzy association rules.

Keywords

data mining; fuzzy set theory; statistical distributions; cumulative probability distribution approach; fusion model; item set level; membership function; multilevel fuzzy association rules; multilevel taxonomy concept; transaction dataset; Association rules; Dairy products; Itemsets; Pragmatics; Probability distribution; Taxonomy; cumulative probability distribution approach (CPDA); multi-level fuzzy association rule;

fLanguage

English

Publisher

ieee

Conference_Titel

Software Engineering, Artificial Intelligence, Networking and Parallel & Distributed Computing (SNPD), 2012 13th ACIS International Conference on

Conference_Location

Kyoto

Print_ISBN

978-1-4673-2120-4

Type

conf

DOI

10.1109/SNPD.2012.36

Filename

6299263