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...
In this paper, we study the behavior of collaborative filtering based recommendations under evolving user profile scenarios. We propose a systematic validation methodology that ...
Olfa Nasraoui, Jeff Cerwinske, Carlos Rojas, Fabio...
There are a number of recommendation systems that can suggest the webpages, within a single website, that other (purportedly similar) users have visited. By contrast, our goal is ...
Recommender systems are used to suggest customized products to users. Most recommender algorithms create collaborative models by taking advantage of web user profiles. In the las...
Elica Campochiaro, Riccardo Casatta, Paolo Cremone...
Search and recommendation systems must include contextual information to effectively model users’ interests. In this paper, we present a systematic study of the effectiveness of...