微型电脑应用

为了挖掘客户价值、有针对性的进行资源分配与产品营销，从客户生命周期的维系流程着手，利用机器学习的GTB算法构建营销预测分类器，采用AJAX及ADO.NET技术设计了4层体系的客户关系管理系统。经实例数据测试系统功能稳定、性能优异、模型预测准确度达到0.90,为商业银行的客户关系管理以及客户价值挖掘提供了理论依据。

In order to dig the customer values, targeted for the allocation of resources and product marketing, this study, starting from the client of the maintenance of the life cycle process, uses GTB algorithm of machine learning to build marketing forecast classifier, uses AJAX and ADO.NET technology to design the system of four levels of customer relationship management system. By the instance data testing the system has stable function and the outstanding performance, the model prediction accuracy reaches 0.90. For the customer relationship management of commercial banks, it provides a theoretical basis for customer value mining.