数据挖掘技术在铁路货运客户细分中的应用

Research of Applying Data Mining in Segmentation of Railway Freight Customers

基于数据挖掘中的聚类和分类技术,通过挖掘货票库中的海量数据所蕴藏的信息,探讨了对铁路货运客户进行细分的方法,先用聚类技术对货运历史数据进行聚类分析,根据聚类结果再用贝叶斯分类器对新数据分类.研究目的是为了根据不同类别的货主对铁路贡献的大小制定不同的优惠措施,并为铁路货运营销部门提供决策依据,提高铁路企业的客户关系管理和决策水平.

Based on the technologies of clustering and classification in data mining, this paper discussed the way of segmentation of railway freight customers by mining the information in mass data of waybill database. That is, we cluster history freight instances using cluster algorithm firstly, and then classify the new instance using Bayesian network classifier according to the results of former steps. The purpose is to set up distinct marketing measures according to the different contribution to railway made by different customers, support the marketing department＇s decision-making, and improve the CRM level of railway enterprises.