欢迎访问中国科学院大学学报,今天是

中国科学院大学学报 ›› 2004, Vol. 21 ›› Issue (3): 358-365.DOI: 10.7523/j.issn.2095-6134.2004.3.012

• 综述 • 上一篇    下一篇

关联规则快速挖掘在CRM中的应用(英文)

王扶东1, 李洁2, 薛劲松1, 朱云龙1   

  1. 1. 中国科学院沈阳自动化研究所, 沈阳理工大学, 沈阳 110016;
    2. 中国科学院沈阳自动化研究所, 沈阳 110168
  • 收稿日期:2003-06-11 修回日期:2004-03-22 发布日期:2004-05-10
  • 基金资助:

    supported by National High tech R&D Plan( 863CIMS2001AA414210,2003AA413021) and NNSF (70171043)

Fast Association Rule Mining in CRM

WANG FuDong1, Li Jie2, XUE JinSong1, ZHU YunLong1   

  1. 1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;
    2. Shenyang Institute of Technology, Shenyang 110168, China
  • Received:2003-06-11 Revised:2004-03-22 Published:2004-05-10

摘要:

交叉销售分析是CRM中的主要分析内容之一。提出了一种前件固定、后件受约束的关联规则快速挖掘算法,该算法的挖掘结果可以帮助企业利用销售情况好的产品促进其他产品的销售;同时提出了一种后件固定、前件受约束的关联规则快速挖掘算法,该算法的挖掘结果可以有效地帮助企业利用交叉销售方法为新产品开拓市场。仿真结果表明,这两种算法能够帮助企业快速准确地得到所需的信息。

关键词: 数据挖掘, 关联规则, 客户关系管理

Abstract:

The analysis of cross selling is one of the important parts in analytical CRM. We present a constraint based association rules mining algorithm AApriori with the specified antecedent and the constrained consequent. The outcome of this algorithm can help enterprises use selling products to popularize products that are unpopular. At the same time, an algorithm CApriori that the consequent is specified and the antecedent is constraind is presented. It can effectively support enterprises to exploit the market of new products. The evaluation demonstrated that the algorithm AApriori and CApriori could quickly get exact information that the enterprise wants.

Key words: data mining, association rule, CRM

中图分类号: