Singular Value Decomposition (SVD), together with the Expectation-Maximization (EM) procedure, can be used to find a low-dimension model that maximizes the loglikelihood of obser...
Sheng Zhang, Weihong Wang, James Ford, Fillia Make...
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
Collaborative filtering systems predict a user's interest in new items based on the recommendations of other people with similar interests. Instead of performing content index...
Jonathan L. Herlocker, Joseph A. Konstan, John Rie...
We show that the standard memory-based collaborative filtering rating prediction algorithm using the Pearson correlation can be improved by adapting user ratings using linear reg...
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...