Most recommendation systems employ variations of Collaborative Filtering (CF) for formulating suggestions of items relevant to users’ interests. However, CF requires expensive co...
Manos Papagelis, Ioannis Rousidis, Dimitris Plexou...
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
Many recommendation systems suggest items to users by utilizing the techniques of collaborative filtering (CF) based on historical records of items that the users have viewed, purc...
Yunhong Zhou, Dennis M. Wilkinson, Robert Schreibe...
Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most infor...
Collaborative Filtering (CF), the prevalent recommendation approach, has been successfully used to identify users that can be characterized as “similar” according to their logg...