A high coherent utility fuzzy itemsets mining algorithm

Author

Chun-Hao Chen ; Ai-Fang Li ; Yeong-Chyi Lee

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Tamkang Univ., Taipei, Taiwan

fYear

2012

fDate

14-16 Aug. 2012

Firstpage

111

Lastpage

114

Abstract

In this paper, we propose an algorithm for mining high coherent utility fuzzy itemsets (HCUFI) from quantitative transactions with the properties of propositional logic. It first transforms quantitative transactions into fuzzy sets. Then, utility of each fuzzy itemsets is then calculated according to the given external utility table. If the value is large than or equals to the minimum utility ratio, it will be considered as a High Utility Fuzzy Itemset (HUFI). Finally, contingency tables are calculated and used for checking those HUFI satisfy specific four criteria or not. If yes, it is a High Coherent Utility Fuzzy Itemsets (HCUFI). Experiments on the foodmart dataset are also made to show the effectiveness of the proposed algorithm.

Keywords

data mining; formal logic; fuzzy set theory; HCUFI mining algorithm; contingency table; fuzzy set theory; high coherent utility fuzzy itemset; propositional logic; Association rules; Educational institutions; Itemsets; Knowledge discovery; Transforms; data mining; fuzzy association rules; fuzzy coherent rules; fuzzy set; membership function;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Security and Intelligence Control (ISIC), 2012 International Conference on

Conference_Location

Yunlin

Print_ISBN

978-1-4673-2587-5

Type

conf

DOI

10.1109/ISIC.2012.6449720

Filename

6449720