1 Tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations....
Abstract. In this paper we propose an incremental item-based collaborative filtering algorithm. It works with binary ratings (sometimes also called implicit ratings), as it is typi...
We investigate two recommendation approaches suitable for online multimedia sharing services. Our first approach, UserRank, recommends items by global interestingness irrespective...
Abstract. This paper describes an approach to product recommendation that combines in a novel way content- and collaborative-based filtering techniques. The system helps the user ...
Francesco Ricci, Adriano Venturini, Dario Cavada, ...
Recommender systems are an emerging technology that helps consumers to find interesting products. A recommender system makes personalized product suggestions by extracting knowle...