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Deep latent factor model for collaborative filtering
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DOI：10.1016/j.sigpro.2019.107366.png)
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Abstract
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Latent factor models have been used widely in collaborative filtering based recommender systems. In recent years, deep learning has been successful in solving a wide variety of machine learning problems. Motivated by the success of deep learning, we propose a deeper version of latent factor model. Experiments on benchmark datasets shows that our proposed technique significantly outperforms all state-of-the-art collaborative filtering techniques. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Deep learning
Latent semantic analysis
Collaborative filtering
Recommender systems
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