计算机技术与发展2013，Vol.23Issue(7)：14-17,21,5.DOI:10.3969/j.issn.1673-629X.2013.07.004
基于数据挖掘的用户忠诚度分析
User Loyalty Analysis Based on Data Mining
摘要
Abstract
User clustering analysis is an important method for network operators to study user behavior and develop their marketing strategies.In this paper,provide a new method,Video-RFM analysis,to cluster the users of an online video system based on the RFM analysis which has been widely used in marketing planning.Cluster the users of PPTV,one of the largest online video providers in China,by Video-RFM model and find out several groups of users with distinguished behavior patterns.Furthermore,quantitatively evaluate customer loyalty of each group of users with Analytic Hierarchy Process (AHP) and provide an efficient algorithm for computing customer loyalty parameter.The results show that Video-RFM analysis is an effective method of mining user behavior and evaluating user loyalty.This clustering method has implications for user behavior analysis while the way to evaluate customer loyalty has practical implications for online video operators.关键词
视频网络/RFM模型/用户聚类分析/层次分析法/用户忠诚度Key words
video network/ RFM model/ user clustering analysis/ AHP/ customer loyalty分类
信息技术与安全科学引用本文复制引用
刘芳,郭宇春..基于数据挖掘的用户忠诚度分析[J].计算机技术与发展,2013,23(7):14-17,21,5.基金项目
国家自然科学基金资助项目(61271199) （61271199）
北京交通大学基础研究基金(W11JB00630) （W11JB00630）
