SLIM - Sparse Linear Methods for Top-N Recommender Systems

SLIM is a software package that implements a set of top-N recommendation methods based on sparse linear models. These models are a generalization to the traditional item-based nearest neighbor collaborative filtering approaches implemented in SUGGEST, and use the historical information to learn a sparse similarity matrix by combining an L2 and L1 regularization approach.

The SLIM software package is available on Github.