EnsVAE: Ensemble Variational Autoencoders for Recommendations
Recommender systems are information software that retrieves relevant items for users from massive sources of data. The variational autoencoder (VAE) has proven to be a promising approach for recommendation systems, as it can explore high-level user-item relations and extract contingencies from the i...
Main Authors: | Ahlem Drif, Houssem Eddine Zerrad, Hocine Cherifi |
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Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9224132/ |
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