GAN‐based deep neural networks for graph representation learning-Reference-Cited by-同舟云学术

GAN‐based deep neural networks for graph representation learning

Published:2022-04-29 Issue:11 Volume:4 Page:
ISSN:2577-8196
Container-title:Engineering Reports
language:en
Short-container-title:Engineering Reports

Author:

Zhao Ming¹²^ORCID,Zhang Yinglong¹^ORCID

Affiliation:

1. School of Physics and Information Engineering Minnan Normal University Zhangzhou Fujian China

2. Fujian Key Laboratory of Granular Computing and Application Minnan Normal University Zhangzhou Fujian China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/eng2.12517

Reference44 articles.

1. YuX RenX SunY et al.Personalized entity recommendation: a heterogeneous information network approach. Proceedings of the 7th ACM International Conference on Web Search and Data Mining; 2014:283‐292.

2. TangJ QuM WangM ZhangM YanJ MeiQ.Line: large‐scale information network embedding. Proceedings of the 24th International Conference on World Wide Web; 2015:1067‐1077.

3. LiuL CheungWK LiX LiaoL. Aligning users across social networks using network embedding. Proceedings of the Twenty‐Fifth International Joint Conference on Artificial Intelligence.2016;1774‐1780.

4. GaoS DenoyerL GallinariP.Temporal link prediction by integrating content and structure information. Proceedings of the 20th ACM International Conference on Information and Knowledge Management; 2011:1169‐1174.

5. TangJ AggarwalC LiuH.Node classification in signed social networks. Proceedings of the 2016 SIAM International Conference on Data Mining; 2016:54‐62.

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