A Comprehensive Survey on Graph Summarization With Graph Neural Networks-Reference-Cited by-同舟云学术

A Comprehensive Survey on Graph Summarization With Graph Neural Networks

Published:2024-08 Issue:8 Volume:5 Page:3780-3800
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Shabani Nasrin¹^ORCID,Wu Jia¹^ORCID,Beheshti Amin¹^ORCID,Sheng Quan Z.¹^ORCID,Foo Jin¹^ORCID,Haghighi Venus¹^ORCID,Hanif Ambreen¹^ORCID,Shahabikargar Maryam¹^ORCID

Affiliation:

1. School of Computing, Macquarie University, Sydney, NSW, Australia

Funder

Centre for Applied Artificial Intelligence at Macquarie University

Australian Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9078688/10635096/10382477.pdf?arnumber=10382477

Reference112 articles.

1. Managing and Mining Graph Data

2. Graph Summarization Methods and Applications

3. Summarizing semantic graphs: a survey

4. Discovering large dense subgraphs in massive graphs;Gibson,2005

5. GraSS: Graph Structure Summarization

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Efficient and Automatic Simplification Method for Arbitrary Complex Networks in Mine Ventilation;Mathematics;2024-09-11

2. A Survey of Computationally Efficient Graph Neural Networks for Reconfigurable Systems;Information;2024-06-28

3. Application of semantic analysis in strategic marketing using the mind map tool;Tyumen State University Herald. Social, Economic, and Law Research;2024-04-26

4. Tourism Asset and Spatial Complexity Analyzed Through Graph-Structured Data Analysis;Lecture Notes in Computer Science;2024