On the Power of Gradual Network Alignment Using Dual-Perception Similarities-Reference-Cited by-同舟云学术

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On the Power of Gradual Network Alignment Using Dual-Perception Similarities

Published:2023-12 Issue:12 Volume:45 Page:15292-15307
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Park Jin-Duk¹^ORCID,Tran Cong²^ORCID,Shin Won-Yong¹^ORCID,Cao Xin³^ORCID

Affiliation:

1. School of Mathematics and Computing (Computational Science and Engineering), Yonsei University, Seoul, South Korea

2. Faculty of Information Technology, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam

3. School of Computer Science and Engineering, University of New South Wales, Sydney, Australia

Funder

National Research Foundation of Korea

Korea government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/10308548/10198682.pdf?arnumber=10198682

Reference39 articles.

1. Integrated anchor and social link predictions across social networks;zhang;Proc 24th Int Joint Conf Artif Intell,2015

2. Fast graph representation learning with PyTorch geometric;fey;Proc ICLR Workshop Representation Learn Graphs Manifolds,2019

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