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Deep latent factor model for collaborative filtering

delete2020-04-01
delete38
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OA
AI
A
Aanchal Mongia
N
Neha Jhamb
É
Émilie Chouzenoux
A
Angshul Majumdar *
DOI:10.1016/j.sigpro.2019.107366delete
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摘要

摘要

En 中文
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.
Keyword:
Deep learning
Latent semantic analysis
Collaborative filtering
Recommender systems
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期刊

Signal Processing 封面图
Signal Processing
IF:
3.6
论文数:
10.0K
被引数:
1.7W

机构

I
Indraprastha Institute of Information Technology Delhi
学者数:
933
论文数: 689
被引数: 558
U
Universite Paris Saclay
学者数:
7.3W
论文数: 5.3W
被引数: 540
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