Hybrid approaches to product recommendation based on customer lifetime value and purchase preferences

Authors:
Duen-Ren Liu;Ya-Yueh Shih
Affiliations:
Institute of Information Management, National Chiao Tung University, Hsinchu, 300 Taiwan, ROC;Institute of Information Management, National Chiao Tung University, Hsinchu, 300 Taiwan, ROC and Department of Information Management, Minghsin University of Science and Technology Hsinchu, Taiwa ...
Venue:
Journal of Systems and Software
Year:
2005

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Abstract

Recommending products to attract customers and meet their needs is important in fiercely competitive environments. Recommender systems have emerged in e-commerce applications to support the recommendation of products. Recently, a weighted RFM-based method (WRFM-based method) has been proposed to provide recommendations based on customer lifetime value, including Recency, Frequency and Monetary. Preference-based collaborative filtering (CF) typically makes recommendations based on the similarities of customer preferences. This study proposes two hybrid methods that exploit the merits of the WRFM-based method and the preference-based CF method to improve the quality of recommendations. Experiments are conducted to evaluate the quality of recommendations provided by the proposed methods, using a data set concerning the hardware retail marketing. The experimental results indicate that the proposed hybrid methods outperform the WRFM-based method and the preference-based CF method.