SLIM

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][1], 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[2].

Literature

[SLIM: Sparse Linear Methods for Top-N Recommender Systems, Xia Ning and George Karypis, ICDM , 2011][3]

External links

• [SLIM][4]