供应链金融风险防范中数据挖掘方法的应用  

Application of Data Mining in Prevention of Supply Chain Financial Risks

作　　者：王娇[1] 

机构地区：[1]长春金融高等专科学校,吉林长春130000

出　　处：《物流技术》2013年第11期380-382,共3页Logistics Technology

基　　金：吉林省教育厅"十二五"社会科学研究项目资助(吉教科文合字(2012)第471号)

摘　　要：从数据挖掘的视角研究了供应链金融风险防范的技术问题,针对经销商在供应链金融中的特殊地位,重点应用数据挖掘技术辨析和识别了供应链金融中具有较高还款风险的经销商的属性特征,通过目标类经销商数据的收集、数据整理概化和预相关分析、属性相关性度量、元组合并和结果映射找出了具有较高风险的经销商所具有的相关性较高的属性,并将这种数据挖掘结果与供应链金融运作实践进行了对比,从而验证了其有效性。In this paper, we studied the technical issues in the prevention of supply chain financial risks from the perspective of data mining, then in the view of the special status of the distributors in supply chain financing, we applied the data mining technology to the recognition and identification of the attributes and characteristics of the distributors with relatively high repayment risks in the supply chain financing as well as the attributes of the distributors with comparatively high risks, and at the end, we compared the result yielded by the data mining technology with the practical operation of the supply chain to demonstrate the validity of the method.

关 键 词：供应链金融 风险防范 数据挖掘 还款风险 

分 类 号：F830.5[经济管理—金融学]