In recommender systems, user ratings of items are often represented in terms of linguistic labels such as “fair” or “very good”. We investigate the potential of fuzzy sets...
Collaborative filtering (CF) shares information between users to provide each with recommendations. Previous work suggests using sketching techniques to handle massive data sets i...
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...
We propose a multilayered semantic social network model that offers different views of common interests underlying a community of people. The applicability of the proposed model to...
Traditionally, collaborative filtering (CF) algorithms used for recommendation operate on complete knowledge. This makes these algorithms hard to employ in a decentralized contex...