Data sparsity is a major problem for collaborative filtering (CF) techniques in recommender systems, especially for new users and items. We observe that, while our target data are...
Weike Pan, Evan Wei Xiang, Nathan Nan Liu, Qiang Y...
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
In this paper we propose a novel recommender system which enhances user-based collaborative filtering by using a trust-based social network. Our main idea is to use infinitesimal ...
Context has been recognized as an important factor to consider in personalized Recommender Systems. However, most model-based Collaborative Filtering approaches such as Matrix Fac...
Web-page recommendation is to predict the next request of pages that Web users are potentially interested in when surfing the Web. This technique can guide Web users to find more u...