Collaborative Filtering, considered by many researchers as the most important technique for information filtering, has been extensively studied by both academic and industrial co...
Item-based Collaborative Filtering (CF) algorithms have been designed to deal with the scalability problems associated with traditional user-based CF approaches without sacrificin...
In this paper we present a hybrid filtering algorithm that attempts to deal with low prediction Coverage, a problem especially present in sparse datasets. We focus on Item HyCoV, a...
Manolis G. Vozalis, Angelos I. Markos, Konstantino...
We study a new task, proactive information retrieval by combining implicit relevance feedback and collaborative filtering. We have constructed a controlled experimental setting, ...
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...