Difference between revisions of "Singular value decomposition"

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'''SVD''' refers to '''singular value decomposition''' in linear algebra. However, in the field of collaborative filtering, SVD often means [[matrix factorization]].
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'''SVD''' refers to '''singular value decomposition''' in [[linear algebra]]. However, in the field of [[collaborative filtering]], the term "SVD" often refers to [[matrix factorization]].
  
 
== SVD in Math ==
 
== SVD in Math ==
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It is also named '''latent semantic indexing''' ('''LSI''') in [[information retrieval]].
 
It is also named '''latent semantic indexing''' ('''LSI''') in [[information retrieval]].
  
== SVD as Matrix Factorization ==
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== See also ==
Please refer to [[Matrix factorization]]
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* [[SVD++]] is a generalization of matrix factorization to make use of [[implicit feedback]].
 
 
== See Also ==
 
* [[SVD++]] is a generalization of matrix factorization to make use of implicit feedback.
 
  
 
== External links ==
 
== External links ==
 
* [[Wikipedia: Singular value decomposition]]
 
* [[Wikipedia: Singular value decomposition]]
 
* [[Wikipedia: Latent semantic indexing]]
 
* [[Wikipedia: Latent semantic indexing]]
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* [http://thatsmaths.com/2013/02/14/singularly-valuable-svd/ Singularly Valuable SVD]
  
 
[[Category: Method]]
 
[[Category: Method]]

Latest revision as of 06:47, 15 February 2013

SVD refers to singular value decomposition in linear algebra. However, in the field of collaborative filtering, the term "SVD" often refers to matrix factorization.

SVD in Math

The traditional SVD can also be used as collaborative filtering algorithm. It is also named latent semantic indexing (LSI) in information retrieval.

See also

External links