Difference between revisions of "SLIM"

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'''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 [http://glaros.dtc.umn.edu/gkhome/slim/overview?q=suggest/overview SUGGEST], and use the historical information to learn a sparse similarity matrix by combining an L2 and L1 regularization approach.
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'''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 [http://glaros.dtc.umn.edu/gkhome/slim/overview?q=suggest/overview 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 [http://www-users.cs.umn.edu/~xning/slim/html/ here].
 
 
 
  
 
== Literature ==
 
== Literature ==
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[[Category:Software]]
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[[Category: Software]]

Latest revision as of 06:11, 4 April 2013

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.

Literature

External links