In this paper we present the results of an experiment made with our e-librarian service ”MatES”, an e-Learning tool on fractions in mathematics. MatES allows students to enter...
In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spec...
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Kons...
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Online news reading has become very popular as the web provides access to news articles from millions of sources around the world. A key challenge of news websites is to help user...
In the Netflix Prize competition many new collaborative filtering (CF) approaches emerged, which are excellent in optimizing the RMSE of the predictions. Matrix factorization (M...