Online communities that allow their users to express their personal preferences, such as the members they trust and the products they appreciate, are becoming increasingly popular...
Server-based collaborative filtering systems have been very successful in e-commerce and in direct recommendation applications. In future, they have many potential applications in...
This paper presents an architecture that helps users to collect and qualify meta-information about web resources within a weblog and then share them with a group of people. Our arc...
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...