期刊文献+

数据挖掘技术在证券客户关系中的应用 被引量:3

Data Mining Technologies in the Security Customer Relationships
下载PDF
导出
摘要 研究证券管理问题,客户关系管理系统(CRM)是现代经营管理科学与现代信息技术结合的科学问题。数据挖掘技术是有效地利用现有数据资源的重要手段。重点是针对数据挖掘技术在证券客户关系管理中的具体问题。运用数据仓库技术建立了客户交易行为数据仓库,并运用聚类技术完成了基于证券公司客户交易行为数据仓库的证券公司客户细分。基于数据挖掘的CRM是对传统企业管理思想的一个创新,充分体现了管理的科学性和艺术性。对企业的经营决策和客户关系管理都具有相当重要的作用和意义。 Customer relationship management (CRM) system is the application of information technology in modern business management. Data mining technology is an important means for effectively using existing data resources. This article emphatically is discusses concrete application of data mining technology in security customer relation management. It constructs a customer transaction data warehouse using data warehouses kill, and based on the cus- tomer transaction data warehouse in security company, it clusters the customer segmentation using data mining skill. This research is of great significance to enterprise's operating decisions and the customer relation management.
作者 叶良
机构地区 苏州市职业大学
出处 《计算机仿真》 CSCD 北大核心 2009年第12期270-273,共4页 Computer Simulation
关键词 数据挖掘 数据仓库 客户关系管理 证券公司 Data mining Data warehouse Customer relationship management (CRM) Security company
  • 相关文献

参考文献6

二级参考文献18

  • 1[5]Han Jiawei,Kamber M.Data mining:concepts and techniques.Morgan Kaufmann Publishers,2000
  • 2Han J W,Kamber M.Data Mining:Concepts and Techniques.Morgan Kanfmann Publishers,Simo Fraser University, 2000.
  • 3Kamber M, Winstone L, Gong Wet al.Generalization and Decision Tree Induction:Efficient Classification in Data Mining.In :Proc. 1997 Int.Workshop Research Issues on Data Engineering(RIDE'97), Birminghan, England. 1997.
  • 4Utgoff P E, Berkman N C, Clouse J A.Decision tree induction based on efficient tree restructuring.Machine Learning, 1997;29(5).
  • 5Shih Y S.Families of splitting criteria for classification trees.Statistics and Computing, 1999;(9).
  • 6Domingos P, Pazzani M.Beyond independence : Conditions for the Optimality of the Simple Bayesian Classifier.In:Proc. 13^th Intl.Conf.Machine Learning, Bari, Italy, Morgan Kautmann, 1996.
  • 7John G H.Enhancements to the Data Mining Process.Ph.D.Thesis, Computer Science Dept, Stanford University, 1997.
  • 8Jensen F V.An Introduction to Bayesian Networks.New York : Springer Verlag, 1996.
  • 9Russell S, Norvig P.Artificial Intelligence :A Modern Aproach.Englewood Cliffs, NJ : Prentice-Hall, 1995.
  • 10Russell S,Binder J,Koller D et al.Local Learning in Probabilistic Networks with Hidden Variables.In : Proc. 14^th Joint Int.Conf.On Artificial Intelligence(IJCAI'95),Volume 2,Montreal, Canada, 1995.

共引文献128

同被引文献14

引证文献3

二级引证文献24

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