Fuzzy QMD Algorithm for Mining Fuzzy Association Rules

被引：0
|
作者：
Wang, Chien-Hua [1 ]
Lee, Wei-Hsuan [2 ]
Yeh, Chia-Hsuan [2 ]
Pang, Chin-Tzong [2 ,3 ]
机构：
[1] Fujian Univ Technol, Sch Management, 3 Xueyuan Rd, Fuzhou 350118, Fujian, Peoples R China
[2] Yuan Ze Univ, Dept Informat Management, 135 Yuan Tung Rd, Taoyuan 32003, Taiwan
[3] Yuan Ze Univ, Innovat Ctr Big Data & Digital Convergence, 135 Yuan Tung Rd, Taoyuan 32003, Taiwan
来源：
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON COMMUNICATION AND INFORMATION PROCESSING (ICCIP 2017) | 2017年
关键词：
Association rule; fuzzy partition; QMD (Quick modulized decomposition); MAP modulized;
D O I：
10.1145/3162957.3162986
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Association rules mining is to find associations efficiently among the different items of a transaction database. In order to help decision-makers conduct sound and timely solutions, we apply fuzzy partition method and combine QMD (Quick Modulized Decomposition) to propose a novel fuzzy data mining method. The proposed method is mainly generated fuzzy itemsets by MAP modulized, and uses fuzzy minimal fuzzy support and minimum fuzzy confidence to generate fuzzy association rules. The method only needs to scan whole transaction database once and uses this modulized method to increase the performance of mining process. Furthermore, in fuzzy partition, the linguistic values of each fuzzy grid were obtained easily and the decision maker makes correct business decisions for marketing strategies.
引用
收藏
页码：50 / 54
页数：5
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