TY - JOUR
T1 - Mining customer preference ratings for product recommendation using the support vector machine and the latent class model
AU - Cheung, Kwok Wai
AU - Kwok, James T.
AU - Law, Martin H.
AU - Tsui, Kwok Ching
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2000
Y1 - 2000
N2 - As Internet commerce becomes more popular, customers' preferences on various products can now be readily acquired on-line via various e-commerce systems. Properly mining this extracted data can generate useful knowledge for providing personalized product recommendation services. In general, recommender systems use two complementary techniques. Content-based systems match customer interests with products attributes, while collaborative filtering systems utilize preference ratings from other customers. In this paper, we address some problems faced by these two systems, and study how machine learning techniques, namely the support vector machine and the latent class model, can be used to alleviated them.
AB - As Internet commerce becomes more popular, customers' preferences on various products can now be readily acquired on-line via various e-commerce systems. Properly mining this extracted data can generate useful knowledge for providing personalized product recommendation services. In general, recommender systems use two complementary techniques. Content-based systems match customer interests with products attributes, while collaborative filtering systems utilize preference ratings from other customers. In this paper, we address some problems faced by these two systems, and study how machine learning techniques, namely the support vector machine and the latent class model, can be used to alleviated them.
UR - http://www.scopus.com/inward/record.url?scp=4544247588&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:4544247588
SN - 1470-6326
VL - 2
SP - 601
EP - 610
JO - Management Information Systems
JF - Management Information Systems
T2 - Second International Conference on Data Mining, Data Minig II
Y2 - 5 July 2000 through 7 July 2000
ER -