SLIM - Sparse Linear Methods for Top-N Recommender Systems

Current version: 1.0, 12/27/2012

SLIM is a library 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 library can be downloaded from here.