Matrix Factorization Techniques for Recommender Systems
Y. Koren, R. Bell, und C. Volinsky.
Computer 42 (8): 30--37 (August 2009)

As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels.

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@article{koren2009matrix,
  abstract = {As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels.},
  added-at = {2012-12-10T09:29:10.000+0100},
  author = {Koren, Y. and Bell, R. and Volinsky, C.},
  biburl = {https://puma.uni-kassel.de/bibtex/259ab9b2678949949c04b0fe2a431585a/jaeschke},
  doi = {10.1109/MC.2009.263},
  interhash = {cface72aeba6ee8c561ccd15035d0ead},
  intrahash = {59ab9b2678949949c04b0fe2a431585a},
  issn = {0018-9162},
  journal = {Computer},
  keywords = {factorization matrix recommender stair},
  month = aug,
  number = 8,
  pages = {30--37},
  timestamp = {2012-12-14T09:58:42.000+0100},
  title = {Matrix Factorization Techniques for Recommender Systems},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5197422&tag=1},
  volume = 42,
  year = 2009
}

%0 Journal Article
%1 koren2009matrix
%A Koren, Y.
%A Bell, R.
%A Volinsky, C.
%D 2009
%J Computer
%K factorization matrix recommender stair
%N 8
%P 30--37
%R 10.1109/MC.2009.263
%T Matrix Factorization Techniques for Recommender Systems
%U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5197422&tag=1
%V 42
%X As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels.

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Matrix Factorization Techniques for Recommender Systems
Y. Koren, R. Bell, und C. Volinsky.
Computer 42 (8): 30--37 (August 2009)

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PUMA

Matrix Factorization Techniques for Recommender SystemsY. Koren, R. Bell, und C. Volinsky. Computer 42 (8): 30--37 (August 2009)

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Matrix Factorization Techniques for Recommender Systems
Y. Koren, R. Bell, und C. Volinsky.
Computer 42 (8): 30--37 (August 2009)