Difference between revisions of "Singular value decomposition"
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== See Also == | == See Also == | ||
* [[SVD++]] is a generalization of matrix factorization to make use of implicit feedback. | * [[SVD++]] is a generalization of matrix factorization to make use of implicit feedback. | ||
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Revision as of 03:37, 12 November 2011
SVD refers to singular value decomposition in linear algebra. However, in the field of collaborative filtering, SVD often means Matrix factorization.
SVD in Math
The traditional SVD can also be used as collaborative filtering algorithm. It's also named Latent Semantic Indexing(LSI) in IR.
- Wikipedia page about SVD: http://en.wikipedia.org/wiki/Singular_value_decomposition
- Wikipedia page about LSI: http://en.wikipedia.org/wiki/Latent_semantic_indexing
SVD as Matrix Factorization
Please refer to Matrix factorization
See Also
- SVD++ is a generalization of matrix factorization to make use of implicit feedback.
