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Investigation of various matrix factorization methods for large recommender systems

, , , and . Proceedings of the 2nd KDD Workshop on Large Scale Recommender Systems and the Netflix Prize Competition, (August 2008)

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Visualization of movie features in collaborative filtering., , , and . SoMeT, page 229-233. IEEE, (2013)Scalable Collaborative Filtering Approaches for Large Recommender Systems., , , and . J. Mach. Learn. Res., (2009)Fast als-based matrix factorization for explicit and implicit feedback datasets., , and . RecSys, page 71-78. ACM, (2010)Recommending new movies: even a few ratings are more valuable than metadata., and . RecSys, page 93-100. ACM, (2009)Investigation of Various Matrix Factorization Methods for Large Recommender Systems., , , and . ICDM Workshops, page 553-562. IEEE Computer Society, (2008)Faktorizáció alapú nagy léptékű ajánló algoritmusok. Budapest University of Technology and Economics, Hungary, (2010)Matrix factorization and neighbor based algorithms for the netflix prize problem., , , and . RecSys, page 267-274. ACM, (2008)Applications of the conjugate gradient method for implicit feedback collaborative filtering., , and . RecSys, page 297-300. ACM, (2011)Computational Complexity Reduction for Factorization-Based Collaborative Filtering Algorithms., and . EC-Web, volume 5692 of Lecture Notes in Computer Science, page 229-239. Springer, (2009)Investigation of various matrix factorization methods for large recommender systems, , , and . Proceedings of the 2nd KDD Workshop on Large Scale Recommender Systems and the Netflix Prize Competition, (August 2008)