期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2017
卷号：6
期号：1
页码：66-68
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Mostly commercial systems are based onCollaborative Filtering (CF). Collaborative Filtering (CF) isan effective and widely adopted recommendation approach.Different from content-based recommender systems whichrely on the profiles of users and items for predictions, CFapproaches make predictions by only utilizing the user-iteminteraction information such as transaction history or itemsatisfaction expressed in ratings, etc. In this study, we developan efficient collaborative filtering method, called RecTree(which stands for RECommendation Tree) that addresses thescalability problem with a divide-and-conquer approach. Anovel product recommendation method called TCRec is alsostudied, which takes advantage of consumer rating historyrecord, social-trust network and product category informationsimultaneously. Motivated by the observation, in this paper,we studied a novel Domain-sensitive Recommendation(DsRec) algorithm, to make the rating prediction by exploringthe user-item subgroup analysis simultaneously.
