企业CRM系统中联机分析挖掘的应用与实现

OLAP与数据挖掘工具由于内在技术以及适用范围的不同,在决策分析中必须协调使用才能发挥最佳的作用。本文提出基于Agent的OLAM(OLAP Mining)模型,将数据挖掘和OLAP技术结合在一个统一的框架之中。提出广义数据空间的概念,使得数据挖掘能够在数据库或数据仓库的不同部位或不同的抽象级别上,对数字数据或者文本数据进行挖掘,加强了决策分析的功能和灵活性。最后,把基于Agent的OLAM模型应用于构建智能CRM,此模型把Agent本身的特点自然地引入到数据挖掘过程中,使数据挖掘系统具有了自治性、自动反应性、交互性、适应环境性等智能特点,有助于在大型数据库和数据仓库中交互式地挖掘多层次多维的知识和联系。

Application and performance of OLAM in enterprise CRM system

Because OLAP and DM have some differences in the inner technology and the range of application,they must be used coordinately in decision analysis to make full use of its best function.Based on Agent's OLAM model,DM and OLAP technology was integrated under a vnited frame.A concept of broad sense data space was proposed so that DM can be made in different part and different abstract hierarchy in database and data warehouse,which enhances the functions and flexibility.Finally,the model was applied on construting intelligent CRM which combines the characteristics of Agent with DM.The DM system has intelligence features such as autonomy,auto reaction,interaction quality,adaptability and so on,which contributes to mining multidimensional and multilevel data interactively in large database and data warehouse.