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Deep Matrix Factorization Models for Recommender Systems

Deep Matrix Factorization Models for Recommender Systems Hong-Jian Xue, Xin-Yu Dai, Jianbing Zhang, Shujian Huang, Jiajun ChenNational Key Laboratory for Novel Software Technology; Nanjing University, Nanjing 210023, ChinaCollaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210023, Systems usually make personalizedrecommendation with user-item interaction ratings,implicit feedback and auxiliary information. Ma-trix Factorization is the basic idea to predict a per-sonalized ranking over a set of items for an indi-vidual user with the similarities among users anditems.

recommendation with user-item interaction ratings, implicit feedback and auxiliary information. Ma-trix factorization is the basic idea to predict a per-sonalized ranking over a set of items for an indi-vidual user with the similarities among users and items. In this paper, we propose a novel matrix factorization model with neural network ...

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