Node Significance Analysis in Complex Networks Using Machine Learning and Centrality Measures-Reference-Cited by-同舟云学术

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Node Significance Analysis in Complex Networks Using Machine Learning and Centrality Measures

Published:2024 Issue: Volume:12 Page:10186-10201
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hajarathaiah Koduru¹^ORCID,Enduri Murali Krishna²^ORCID,Anamalamudi Satish²,Abdul Ashu³^ORCID,Chen Jenhui⁴^ORCID

Affiliation:

1. School of Computer Science and Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India

2. Department of Computer Science and Engineering, Algorithms and Complexity Theory Laboratory, SRM University-AP, Amaravati, India

3. Department of Computer Science and Engineering, Centre for Computational and Integrative Sciences, SRM University-AP, Amaravati, India

4. Department of Computer Science and Information Engineering, Chang Gung University, Guishan, Taoyuan, Taiwan

Funder

National Science and Technology Council, Taiwan

Chang Gung Memorial Hospital, Taoyuan, Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10401904.pdf?arnumber=10401904

Reference55 articles.

1. Online Social Networks: Status and Trends

2. Online social networks: A survey of a global phenomenon

3. Centrality in social networks conceptual clarification

4. A faster algorithm for betweenness centrality*

5. Ranking of Closeness Centrality for Large-Scale Social Networks

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