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...
Collaborative Filtering (CF) recommendations are computed by leveraging a historical data set of users’ ratings for items. It assumes that the users’ previously recorded ratin...
Memory-based methods for collaborative filtering predict new ratings by averaging (weighted) ratings between, respectively, pairs of similar users or items. In practice, a large ...
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
We present a mathematical model for network routing based on generating paths in a consistent direction. Our development is based on an algebraic and geometric framework for defini...