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基于数据挖掘的用户忠诚度分析 被引量：3

User Loyalty Analysis Based on Data Mining
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摘要 用户聚类分析是数据挖掘中的重要手段。文中根据视频应用的特点,在传统的RFM模型基础上,提出一种根据用户观看行为对用户进行聚类的方法:Video-RFM聚类法。利用该方法,文中对中国最大的网络电视运营商PPTV的客户端用户进行了聚类分析。在此基础上,提出了一套将Video-RFM聚类法所使用的用户行为指标,映射到用户忠诚度指数的有效方法。经过实际数据验证发现,Video-RFM方法能够成功地区分行为差异较大的用户群,同时也能够很好地区分用户忠诚度。文中提出的聚类方法对了解视频系统的用户行为具有普遍的参考价值。文中对用户忠诚度的定量研究,对企业优化产品质量具有实际意义。 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 Vide- o-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.
作者 刘芳 郭宇春
机构地区 北京交通大学电子信息工程学院
出处 《计算机技术与发展》 2013年第7期14-17,21,共5页 Computer Technology and Development
基金 国家自然科学基金资助项目(61271199) 北京交通大学基础研究基金(W11JB00630)
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 video network RFM model user clustering analysis AHP customer loyalty
分类号 TP31 [自动化与计算机技术—计算机软件与理论]
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参考文献13

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共引文献273

同被引文献12

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二级引证文献2

计算机技术与发展
2013年 第7期

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