Two-step hybrid collaborative filtering using deep variational Bayesian autoencoders

Existing recommender systems rely on user and item representations in a fixed continuous low-dimensional latent space. To predict ratings, they use only an implicit feedback matrix, whereas user and item side information is ignored. Furthermore, they use the same arbitrary priors for the user and it...

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Bibliographic Details

Published in:	Information sciences Vol. 562; pp. 136 - 154
Main Authors:	Nahta, Ravi, Meena, Yogesh Kumar, Gopalani, Dinesh, Chauhan, Ganpat Singh
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.07.2021
Subjects:	Attributes Collaborative filtering Neural networks Recommender systems Variational autoenocoders Variational inference Attributes Variational autoenocoders Variational inference Collaborative filtering Neural networks Recommender systems
ISSN:	0020-0255, 1872-6291
Online Access:	Get full text
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