Collaborative filtering (CF) allows the preferences of multiple users to be pooled to make recommendations regarding unseen products. We consider in this paper the problem of onl...
Craig Boutilier, Richard S. Zemel, Benjamin M. Mar...
We discuss learning a profile of user interests for recommending information sources such as Web pages or news articles. We describe the types of information available to determin...
In this work, we present an extension of CORE [2], a tool for Collaborative Ontology Reuse and Evaluation. The system receives an informal description of a specific semantic domai...
With the increasing popularity of recommender systems in commercial services, the quality of recommendations has increasingly become an important to study, much like the quality o...
Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...