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

@article{citeulike:3031960, 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.}, author = {Liu, Duen-Ren and Shih, Ya-Yueh}, citeulike-article-id = {3031960}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.jss.2004.08.031}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6V0N-4DGYJRP-1/1/7c8420136ad0d5fa069c92fc836a421a}, doi = {10.1016/j.jss.2004.08.031}, journal = {Journal of Systems and Software}, keywords = {recommender}, month = {August}, number = {2}, pages = {181--191}, posted-at = {2008-07-22 07:57:30}, priority = {3}, title = {Hybrid approaches to product recommendation based on customer lifetime value and purchase preferences}, url = {http://dx.doi.org/10.1016/j.jss.2004.08.031}, volume = {77}, year = {2005} }

TY - JOUR ID - citeulike:3031960 L3 - citeulike-article-id:3031960 N2 - 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. IS - 2 JF - Journal of Systems and Software EP - 191 TI - Hybrid approaches to product recommendation based on customer lifetime value and purchase preferences VL - 77 SP - 181 KW - recommender AU - Liu, Duen-Ren AU - Shih, Ya-Yueh PY - 2005/08// UR - http://dx.doi.org/10.1016/j.jss.2004.08.031 ER -