Deep latent factor model for collaborative filtering - Archive ouverte HAL
Article Dans Une Revue Signal Processing Année : 2020

Deep latent factor model for collaborative filtering

Résumé

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.
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Dates et versions

hal-02373934 , version 1 (22-11-2019)

Identifiants

Citer

Aanchal Mongia, Neha Jhamb, Emilie Chouzenoux, Angshul Majumdar. Deep latent factor model for collaborative filtering. Signal Processing, 2020, 169, pp.107366. ⟨10.1016/j.sigpro.2019.107366⟩. ⟨hal-02373934⟩
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