標題: Hybrid approaches to product recommendation based on customer lifetime value and purchase preferences
作者: Liu, DR
Shih, YY
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: recommender system;data mining;product recommendation;customer lifetime value (CLV);collaborative filtering
公開日期: 1-Aug-2005
摘要: 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. (c) 2004 Elsevier Inc. All rights reserved.
URI: http://dx.doi.org/10.1016/j.jss.2004.08.031
http://hdl.handle.net/11536/13415
ISSN: 0164-1212
DOI: 10.1016/j.jss.2004.08.031
期刊: JOURNAL OF SYSTEMS AND SOFTWARE
Volume: 77
Issue: 2
起始頁: 181
結束頁: 191
Appears in Collections:Articles


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