A novel Enhanced Collaborative Autoencoder with knowledge distillation for top-N recommender systems

In most recommender systems, the data of user feedbacks are usually represented with a set of discrete values, which are difficult to exactly describe users’ interests. This problem makes it not easy to exactly model users’ latent preferences for recommendation. Intuitively, a basic idea for this is...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 332; S. 137 - 148
Hauptverfasser:	Pan, Yiteng, He, Fazhi, Yu, Haiping
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 07.03.2019
Schlagworte:	Denoising Autoencoder Knowledge distillation Neural network Recommender system Neural network Knowledge distillation Recommender system Denoising Autoencoder
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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