An Exploration of the Recommender Systems in E-Commerce
Qingsheng Zhu · Computer Engineering and Science · 2004
E-Commerce companies compete each other nowadays, and one key to winning the competition is to get knowledge about customers' consuming preferences so as to establish better adequate personalized services to satisfy the customers. On this background, recommender systems gradually develops, supported by the agent technologies derived from Artificial Intelligence. The technologies to educe recommendation and their modes of representation are explored in this paper, afterwards similarities and differences among mainstream recommendation technologies and their application ranges are analyzed. At last, a hybrid recommender system technology is deeply investigated.