A detection algorithm of customer outlier data based on data mining technology

摘要：

　　For the outlier data detection problem of customer transactional retail data in a large-scale chain supermarket,customer transaction data are detected by data mining technology and database technology,the sample data of abnormal customer behavior have been chosen in the customer transaction database,the abnormal customer behavior will be found out for outlier samples data fusion by the Dempster/Shafer evidence theory.The experimental result shows that the algorithm is more accurate and efficient than other algorithms to detect abnormal customer transactional retail behavior by the Dempster/Shafer evidence theory.

关键词： outlier membership data dempster/shafer evidence theory algorithm data fusion

作者: Jia Ren

作者单位: Xian Fanyi University,Xian,Shaanxi,China

会议类型: 国际会议

会议名称: 2017年经济与企业管理国际学术会议(FEBM2017)

会议地点: 上海

会议语种:英文

页码: 272-278

在线出版日期: 2017-10-21（万方平台首次上网日期，不代表论文的发表时间）