A correlative denoising autoencoder to model social influence for top- N recommender system

In recent years, there are numerous works been proposed to leverage the techniques of deep learning to improve social-aware recommendation performance. In most cases, it requires a larger number of data to train a robust deep learning model, which contains a lot of parameters to fit training data. H...

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Bibliographic Details
Published in:	Frontiers of Computer Science Vol. 14; no. 3; p. 143301
Main Authors:	PAN, Yiteng, HE, Fazhi, YU, Haiping
Format:	Journal Article
Language:	English
Published:	Beijing Higher Education Press 01.06.2020 Springer Nature B.V
Subjects:	Algorithms Artificial neural networks Computer Science Correlation Deep learning denoising autoencoder Machine learning Mathematical models neural network Noise reduction Parameters recommender system Recommender systems Regularization Research Article Robustness social network Social networks social network recommender system denoising autoencoder neural network
ISSN:	2095-2228, 2095-2236
Online Access:	Get full text
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