A High Coherent Utility Fuzzy Itemsets Mining Algorithm

被引：0
|
作者：
Chen, Chun-Hao [1 ]
Li, Ai-Fang [1 ,2 ]
Lee, Yeong-Chyi [3 ]
机构：
[1] Tamkang Univ, Dept Comp Sci & Informat Engn, Taipei, Taiwan
[2] Tamkang Univ, Dept Comp Sci & Informat Engn, Taipei, Taiwan
[3] Cheng Shiu Univ, Dept Informat Management, Kaohsiung, Taiwan
来源：
THIRD INTERNATIONAL CONFERENCE ON INFORMATION SECURITY AND INTELLIGENT CONTROL (ISIC 2012) | 2012年
关键词：
fuzzy set; fuzzy association rules; fuzzy coherent rules; membership function; data mining; ASSOCIATION RULES;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：111 / 114
页数：4
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