Mining Statistically Significant Communities from Weighted Networks-Reference-Cited by-同舟云学术

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Mining Statistically Significant Communities from Weighted Networks

Published:2022 Issue: Volume: Page:1-1
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

He Zengyou¹,Chen Wenfang²,Wei Xiaoqi²,Liu Yan³

Affiliation:

1. School of Software, Dalian University of Technology, Dalian, Liaoning, China, 116620

2. School of Software, Dalian University of Technology, 12399 Dalian, Liaoning, China

3. School of Software, Dalian University of Technology, Dalian, Liaoning, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/4358933/09779964.pdf?arnumber=9779964

Reference61 articles.

1. Validation of community robustness

2. Up-to-date catalogues of yeast protein complexes

3. Measuring the significance of community structure in complex networks

4. Detecting overlapping protein complexes in protein-protein interaction networks

5. A generalised significance test for individual communities in networks

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1. A Framework for Accurate Community Detection on Signed Networks Using Adversarial Learning;IEEE Transactions on Knowledge and Data Engineering;2023

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