An Integrated Recommender Method Based on CLV and Collaborative Filtering
Zhang Huiying1, Xue Fuliang1,2
1. College of Management & Economics, Tianjin University, Tianjin 300072, China;
2. Business School, Tianjin University of Finance & Economics, Tianjin 300222, China
Abstract：In this paper, an integrated recommender method which employs weighted RFM and CF method is presented. Firstly,CF is applied to customer ratings on products, which are collected implicitly by Web usage mining approach,then weighted RFM is applied to improve similar user clustering to find recommend rule effectively and generate better quality recommendations. Product Taxonomy (PT) is also used to preprocess products according to their categories and to reduce dimensions of computational space. Evaluation results show that the proposed method is more effective both in the accuracy and relevance of recommendations.
张慧颖, 薛福亮. 一种集成客户终身价值与协同过滤的推荐方法[J]. 现代图书情报技术, 2012, 28(1): 46-52.
Zhang Huiying, Xue Fuliang. An Integrated Recommender Method Based on CLV and Collaborative Filtering. New Technology of Library and Information Service, 2012, 28(1): 46-52.
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