Title :
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
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;
Conference_Titel :
Information Security and Intelligence Control (ISIC), 2012 International Conference on
Conference_Location :
Yunlin
Print_ISBN :
978-1-4673-2587-5
DOI :
10.1109/ISIC.2012.6449720
