The open nature of collaborative recommender systems present a security problem. Attackers that cannot be readily distinguished from ordinary users may inject biased profiles, deg...
Recommender systems based on collaborative filtering predict user preferences for products or services by learning past user-item relationships. A predominant approach to collabo...
Collaborative filtering systems predict a user's interest in new items based on the recommendations of other people with similar interests. Instead of performing content index...
Jonathan L. Herlocker, Joseph A. Konstan, John Rie...
This paper presents a detailed study of the behavior of three different content-based collaborative filtering metrics (correlation, cosine and mean squared difference) when they a...
In recommender systems, user ratings of items are often represented in terms of linguistic labels such as “fair” or “very good”. We investigate the potential of fuzzy sets...