Abstract. Recommender systems produce social networks as a side effect of predicting what users will like. However, the potential for these social networks to aid in recommending i...
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
—In this paper, we propose a Bayesian-inference based recommendation system for online social networks. In our system, users share their content ratings with friends. The rating ...
In this paper we propose a novel recommender system which enhances user-based collaborative filtering by using a trust-based social network. Our main idea is to use infinitesimal ...
The new social media sites--blogs, wikis, Flickr and Digg, among others--underscore the transformation of the Web to a participatory medium in which users are actively creating, e...