SDAE-LFM: A Latent Factor Model for Recommendation Based on Stack Denoising AutoEncoder

Recommendation methods usually associated with data sparsity. The traditional recommendation methods take the users' rating information as the recommendation basis, which ignore the latent features that can be taking into consideration to model for better recommendations. In order to deal with...

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Veröffentlicht in:	Journal of physics. Conference series Jg. 1646; H. 1; S. 12151 - 12157
Hauptverfasser:	Luo, Jianyan, Xing, Xing, Zheng, Hang, Xin, Mindong, Jia, Zhichun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bristol IOP Publishing 01.09.2020
Schlagworte:	Algorithms Deep learning Feature extraction Machine learning Noise reduction Physics Recommender systems
ISSN:	1742-6588, 1742-6596
Online-Zugang:	Volltext
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