期刊文献+

数据挖掘技术在客户关系管理中的应用研究

The application of data-mining technology to the researchon the customer relationship management
下载PDF
导出
摘要 从市场竞争的现状出发,阐述了数据挖掘技术原理,重点探讨了FCM聚类算法和关联规则,并将其运用到电信客户关系挖掘中,对具体公司移动客户消费数据进行了详细分析。 Taking the current situations of market competition into consideration, we expatiated the principle of data- mining technology before we focused on the FCM clustering algorithm and association rules which were used to mine the telecommunication customer relationship. Meanwhile, we also analyzed some specific experimental data of mobile customers in detail.
作者 张福泉
出处 《佛山科学技术学院学报(自然科学版)》 CAS 2011年第6期62-65,共4页 Journal of Foshan University(Natural Science Edition)
关键词 数据挖掘 客户关系 聚类算法 data mining customer relationship clustering algorithm
  • 相关文献

参考文献3

  • 1李靖.客户关系管理:从概念走向实用功能模块[N].人民邮电报,2001-12-06(7).
  • 2范明.孟小峰.数据挖掘:概念与技术[M].北京:机械工业出版社,2007.
  • 3郑建国,周明全,耿国华.智能数据挖掘理论体系研究[J].西安电子科技大学学报,2004,31(1):143-147. 被引量:4

二级参考文献21

  • 1郑建国,刘芳,焦李成.A Novel Induction Algorithm for DM[J].Journal of Systems Engineering and Electronics,2001,12(4):91-97. 被引量:3
  • 2Sarychev A P. The Optimal Set Features Determination in Discriminant Analysis by the Group Method of Data Handling[J]. SAMS,1998, 23(1-2) : 104-109.
  • 3Heckerman D. Bayesian Networks for Data Mining[J]. Data Mining and Knowledge Discovery, 1997, 1(1): 79-119.
  • 4Rissanen J. Hypothesis Selection and Testing by the MDL Principle[J]. The Computer Journal, 1999, 42(4): 260-269.
  • 5Agrawal R, Mannila H, Srikant R, et al. Fast Discovery of Association Rules[ A ]. Advances in Knowledge Discovery and Data Mining[C]. Menlo Park: AAAI Press, 1996. 307-328.
  • 6Chakrabarti S, Sarawagi S, Dom B. Mining Surprising Patterns Using Temporal Description Length[A]. VLDB[C]. Merdo Park: AAAI Press, 1998. 606-617
  • 7Kleinberg J, Papadimitriou C, Rnghavan P. A Micro-economic View of Data Mining[J]. Data Mining and Knowledge Discover, 1998,2(4): 311-324.
  • 8Boulicaut J F, Klemettinen M, Mannils H. Querying Inductive Databases: a Case Study on the MINE RULE Operator[A]. 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD'98)[C]. Nantes: Nantes Press, 1998. 194-202.
  • 9Boulicaut J F, Klemettinen M, Mannila H. Modeling KDD Porcesses within the Inductive Database Framework[A]. Data Warehousing and Knowledge Discovery(DaWaK 1999)[C]. San Diego:AAAI Press, 1999. 293-302.
  • 10Tickle A B, Andrews R, Golea M, et al. The Truth Will Come to Light: Directions and Challenges in Extracting the Knowledge Embedded Within Trained Artificial Nerual Networks[J]. IEEE Trans on Neural Networks, 1998, 9(10) : 1057-1068.

共引文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部