To mine association rules of customer values via a data mining procedure with improved model: An empirical case study

被引：44
作者：
Chiang, Wen-Yu [1 ]
机构：
[1] Aletheia Univ, Dept Ind & Business Management, Danshui, Taiwan
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2011年 / 38卷 / 03期
关键词：
Association rules; Customer values; RFMDR model; Supervised Apriori algorithm;
D O I：
10.1016/j.eswa.2010.07.097
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes a new procedure and an improved model to mine association rules of customer values. The market of online shopping industry in Taiwan is the research area. Research method adopts Ward's method to partition online shopping market into three markets. Customer values are refined from an improved RFMDR model (based on RFM/RFMD model). Supervised Apriori algorithm is employed with customer values to create association rules. These effective rules are suggested to apply on a customized marketing function of a CRM system for enhancing their customer values to be higher grades. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1716 / 1722
页数：7
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