Deep latent factor model for collaborative filtering
A Mongia, N Jhamb, E Chouzenoux, A Majumdar�- Signal Processing, 2020 - Elsevier
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.
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.
Deep latent factor model for collaborative filtering
A Mongia, N Jhamb, E Chouzenoux… - arXiv preprint arXiv …, 2019 - arxiv.org
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.
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.
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