An Integrated Recommender Method Based on CLV and Collaborative Filtering

doi:10.11925/infotech.1003-3513.2012.01.08

New Technology of Library and Information Service

2012, Vol. 28

Issue (1): 46-52 DOI: 10.11925/infotech.1003-3513.2012.01.08

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An Integrated Recommender Method Based on CLV and Collaborative Filtering

Zhang Huiying¹, Xue Fuliang^1,2

1. College of Management & Economics, Tianjin University, Tianjin 300072, China;
2. Business School, Tianjin University of Finance & Economics, Tianjin 300222, China

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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.

Key words： Recommender system Collaborative filtering Customer lifetime value Product taxonomy

Received: 19 October 2011 Published: 26 February 2012

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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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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2012.01.08 OR https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2012/V28/I1/46

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