@hackage recommender-als0.2.2.0

This package provides a recommendation algorithm based on alternating least squares algorithm, as made famous by the Netflix Prize. . It takes as its input a list of user-item pairs and returns a list of recommendations for each user. The current implementation is limited to using unrated pairs. . The algorithm is parallelized and should be quick enough to train the model within seconds for a few thousand users and items. Getting recommendations from a computed model happens nearly instantly. . For implementation details, see "Large-scale Parallel Collaborative Filtering for the Netflix Prize" by Yunhong Zhou, Dennis Wilkinson, Robert Schreiber and Rong Pan.