Recommender systems aim to substantially reduce information overload by suggesting lists of similar items that users may find interesting. Caching has been a useful technique for...
Umar Qasim, Vincent Oria, Yi-fang Brook Wu, Michae...
Recommending news stories to users, based on their preferences, has long been a favourite domain for recommender systems research. In this paper, we describe a novel approach to n...
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...
We present an incentive-based architecture for providing recommendations in a social network. We maintain a distinct reputation system for each individual and we rely on users to ...
Rajat Bhattacharjee, Ashish Goel, Konstantinos Kol...
This work addresses a particular kind of cross domain personalization task consisting of selecting simultaneously two items in two different domains and recommending them togethe...