摘要
研究数据挖掘算法中的Microsoft聚类算法以及其在金融领域的应用。从海量的数据里挖掘出潜在的信息是数据挖掘的主要工作,通过对客户交易信息的过滤和挖掘,建立起为银行更好地提供智能决策和建议数据挖掘商业应用实例系统。系统的客户端开发选择的是Visual Studio.NET 2008,并使用ADOMD.NET对象及Web控件对模型的结果进行输出展示。用户可以应用这个系统通过输入客户的一些个人属性以及办理业务的基本情况,查看所关心的信誉情况、业务的办理趋向、银行开展新业务的趋向等信息。在整个实例系统的构建过程中,对聚类分析模型的挖掘过程进行了详细的分析,促进了数据挖掘的应用实践。
The application of Microsoft clustering algorithm of data mining in financial field is discussed.The function of the data mining is mining potential information from the massive data.A business data mining system is created based on Microsoft clustering algorithm,which can provide better decisions and recommendations for the bank through filtering and mining the customers＇ transaction information.The client part of system is developed with the Visual Studio.NET 2008.And it uses the objects of ADOMD.NET and Web controls to display the result of mining.By using the application system it can analyze the customer＇s attributes to predict his credit and to predict his business tendency.In the creation of the instance model system the whole program of data mining is introduced in detail and it helps the development of data mining＇s application.
出处
《计算机与现代化》
2012年第4期56-60,共5页
Computer and Modernization
基金
北京市人才强教计划--骨干教师基金资助项目(PHR201008428)
北京市教委科技发展计划基金资助项目(KM201110772013)
北京市优秀人才培养基金资助项目(2010D005007000003)
关键词
聚类分析
数据挖掘
预测
业务趋向
实例系统
clustering algorithm
data mining
prediction
business tendency
application system
