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...
This thesis investigates application of clustering to multi-criteria ratings as a method of improving the precision of top-N recommendations. With the advent of ecommerce sites th...
With the exponential growth of Web contents, Recommender System has become indispensable for discovering new information that might interest Web users. Despite their success in th...
Social network sites rely on the contributions of their members to create a lively and enjoyable space. Recent research has focused on using personalization and recommender techno...
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...
We consider the problem of recommending the best set of k items when there is an inherent ordering between items, expressed as a set of prerequisites (e.g., the course ‘Real Ana...
We examine the case of over-specialization in recommender systems, which results from returning items that are too similar to those previously rated by the user. We propose Outsid...
Zeinab Abbassi, Sihem Amer-Yahia, Laks V. S. Laksh...
This paper presents a new memory-based approach to Collaborative Filtering where the neighbors of the active user will be selected taking into account their predictive capability....
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...