An efficient method for autoencoder‐based collaborative filtering-Reference-Cited by-同舟云学术

An efficient method for autoencoder‐based collaborative filtering

Published:2018-05-18 Issue:23 Volume:31 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Wang Yi‐Lei¹²,Tang Wen‐Zhe²,Yang Xian‐Jun²,Wu Ying‐Jie²^ORCID,Chen Fu‐Ji¹

Affiliation:

1. School of Economics and ManagementFuzhou University Fuzhou China

2. College of Mathematics and Computer ScienceFuzhou University Fuzhou China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.4507

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4. ZhouY WilkinsonD SchreiberR PanR.Large‐scale parallel collaborative filtering for the Netflix prize. Paper presented at: International Conference on Algorithmic Applications in Management;2008;Shanghai China.

5. LeeJ KimS LebanonG SingerY.Local low‐rank matrix approximation. Paper presented at: Proceedings of the 30th International Conference on International Conference on Machine Learning;2013;Atlanta GA.

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