User-Interactive Question Answering (QA) communities such as Yahoo! Answers are growing in popularity. However, as these QA sites always have thousands of new questions posted dai...
Collaborative recommender systems are highly vulnerable to attack. Attackers can use automated means to inject a large number of biased profiles into such a system, resulting in r...
Robin D. Burke, Bamshad Mobasher, Chad Williams, R...
Suppose you buy a new laptop and, simply because you like it so much, you recommend it to friends, encouraging them to purchase it as well. What would be an adequate price for the...
More and more web users keep up with newest information through information streams such as the popular microblogging website Twitter. In this paper we studied content recommendat...
Jilin Chen, Rowan Nairn, Les Nelson, Michael Berns...
This paper discusses the combination of collaborative and contentbased filtering in the context of web-based recommender systems. In particular, we link the well-known MovieLens ...