In this paper I propose a context-aware collaborative filtering system that can predict a user's preference in different context situations based on past user-experiences. Th...
In this work, we apply a clustering technique to integrate the contents of items into the item-based collaborative filtering framework. The group rating information that is obtain...
We propose a fully decentralized collaborative filtering approach that is self-organizing and operates in a distributed way. The relevances between downloading files (items) are...
Jun Wang, Marcel J. T. Reinders, Reginald L. Lagen...
A recommender system suggests the items expected to be preferred by the users. Recommender systems use collaborative filtering to recommend items by summarizing the preferences of...
Data sparsity is a major problem for collaborative filtering (CF) techniques in recommender systems, especially for new users and items. We observe that, while our target data are...
Weike Pan, Evan Wei Xiang, Nathan Nan Liu, Qiang Y...