Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. These vulnerabilities mostly emanate from the open nature of such systems ...
Bamshad Mobasher, Robin D. Burke, Chad Williams, R...
Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. Researchers have shown that attackers can manipulate a system’s reco...
Robin D. Burke, Bamshad Mobasher, Runa Bhaumik, Ch...
Web-based applications with a large variety of users suffer from the inability to satisfy heterogeneous needs. A remedy for the negative effects of the traditional "one-size-...
Paolo Buono, Maria Francesca Costabile, Stefano Gu...
Robustness analysis research has shown that conventional memory-based recommender systems are very susceptible to malicious profile-injection attacks. A number of attack models h...
Collaborative filtering techniques have been successfully employed in recommender systems in order to help users deal with information overload by making high quality personalize...
Paul-Alexandru Chirita, Wolfgang Nejdl, Cristian Z...