%0 Journal Article %1 weimer07 %A Weimer, Markus %A Karatzoglou, Alexandros %A Le, Quoc V. %A Smola, Alex %B Advances in Neural Information Processing Systems %D 2007 %K MMMF cofirank collaborative_filtering ranking %T CoFiRank, Maximum Margin Matrix Factorization for Collaborative Ranking %V 20 %X In this paper, we consider collaborative filtering as a ranking problem. We present a method which uses Maximum Margin Matrix Factorization and optimizes ranking instead of rating. We employ structured output prediction to optimize directly for ranking scores. Experimental results show that our method gives very good ranking scores and scales well on collaborative filtering tasks.

@article{weimer07, abstract = {In this paper, we consider collaborative filtering as a ranking problem. We present a method which uses Maximum Margin Matrix Factorization and optimizes ranking instead of rating. We employ structured output prediction to optimize directly for ranking scores. Experimental results show that our method gives very good ranking scores and scales well on collaborative filtering tasks.}, added-at = {2009-06-22T17:28:38.000+0200}, author = {Weimer, Markus and Karatzoglou, Alexandros and Le, Quoc V. and Smola, Alex}, biburl = {https://www.bibsonomy.org/bibtex/2ea80579c3ec0cc54f705372d0ff8238e/lefteris8}, booktitle = {Advances in Neural Information Processing Systems}, citeulike-article-id = {3152592}, comment = {Predict ranking instead of predict scores.}, interhash = {bbac03ed07f0e3184f084dc0f3bfb901}, intrahash = {ea80579c3ec0cc54f705372d0ff8238e}, keywords = {MMMF cofirank collaborative_filtering ranking}, posted-at = {2008-08-25 03:49:56}, priority = {0}, timestamp = {2009-06-22T17:28:40.000+0200}, title = {CoFiRank, Maximum Margin Matrix Factorization for Collaborative Ranking}, volume = 20, year = 2007 }