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Lecture Notes in Computer Science
We have developed a framework for jointly conducting collaborative filtering and distance metric learning based on regularized singular value decomposition (RSVD), which discovers the user matrix and item matrix in the low rank space. Our approach is able to solve RSVD and simultaneously learn the parameters of Mahalanobis distance considering the ratings given by similar users and dissimilar users. One characteristic of our approach is that the learned model can be effectively applied todoi:10.1007/978-3-319-48051-0_14 fatcat:ntkqzhjjvva45ldymz77d6wivu