The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
Recommender systems based on user feedback rank items by aggregating users’ ratings in order to select those that are ranked highest. Ratings are usually aggregated using a weig...
Florent Garcin, Boi Faltings, Radu Jurca, Nadine J...
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 are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
A recommender system must be able to suggest items that are likely to be preferred by the user. In most systems, the degree of preference is represented by a rating score. Given a...