Collaborative filtering systems help address information overload by using the opinions of users in a community to make personal recommendations for documents to each user. Many c...
Badrul M. Sarwar, Joseph A. Konstan, Al Borchers, ...
Recommender Systems (RS) aim at predicting items or ratings of items that the user are interested in. Collaborative Filtering (CF) algorithms such as user- and item-based methods ...
Karen H. L. Tso-Sutter, Leandro Balby Marinho, Lar...
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...
To solve the sparsity problem in collaborative filtering, researchers have introduced transfer learning as a viable approach to make use of auxiliary data. Most previous transfer...
We consider in this paper a popular class of recommender systems that are based on Collaborative Filtering (CF for short). CF is the process of predicting customer ratings to item...