Similarity of users' (content-based) preference models for Collaborative filtering in few ratings scenario

Collaborative filtering is an efficient way to find best objects to recommend. This technique is particularly useful when there is a lot of users that rated a lot of objects. In this paper, we propose a method that improve the Collaborative filtering in situations, where the number of ratings or users is small. The proposed approach is experimentally evaluated on real datasets with very convincing results. (C) 2012 Published by Elsevier Ltd.