Data Mining Application on Customer Service - Decision Support and Machine Fault Diagnosis

摘要：

In traditional customer service support of a manufacturing environment,a customer service database usually stores two types of service information: (1) unstructured customer service reports record machine problems and its remedial actions and (2) structured data on sales,employees,and customers for day-to-day management operations.This paper investigates how to apply data mining techniques to extract knowledge from the database to support two kinds of customer service activities: decision support and machine fault diagnosis.A data mining process,based on the data mining tool DBMiner,was investigated to provide structured management data for decision support.In addition,a data mining technique that integrates neural network,case-based reasoning,and rule-based reasoning is proposed;it would search the unstructured customer service records for machine fault diagnosis.The proposed technique has been implemented to support intelligent fault diagnosis over the World Wide Web.

关键词： Customer service support Data mining Forecasting Machine fault diagnosis

作者: LIU Tong-na ZhANG Qian

作者单位: Department of Electronic and Communication Engineering.Department of Economic Management,North China Electric Power University,P.R.China,071003

会议类型: 国际会议

会议名称: 2007 International Conference on Management Science and Engineering(2007管理科学与工程国际学术会议)

会议地点: 河南焦作

会议语种:英文

页码: 1086-1092

在线出版日期: 2007-08-20（万方平台首次上网日期，不代表论文的发表时间）