Partition Clustering in Complex Weighted Networks Using K-Cut Ranking and Krill-Herd Optimization-Reference-Cited by-同舟云学术

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Partition Clustering in Complex Weighted Networks Using K-Cut Ranking and Krill-Herd Optimization

Published:2024-09 Issue:5 Volume:11 Page:5035-5044
ISSN:2327-4697
Container-title:IEEE Transactions on Network Science and Engineering
language:
Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Srivastava Vishal¹^ORCID,Singh Shashank Sheshar²^ORCID,Jain Ankush³^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology (MNNIT), Allahabad, Prayagraj, India

2. Department of Computer Science & Engineering, Thapar Institute of Engineering and Technology, Patiala, India

3. Department of Computer Science & Engineering, Netaji Subhas University of Technology, New Delhi, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6488902/10637788/10586817.pdf?arnumber=10586817

Reference20 articles.

1. Network Structural Balance Based on Evolutionary Multiobjective Optimization: A Two-Step Approach

2. A Second-Order Symmetric Non-Negative Latent Factor Model for Undirected Weighted Network Representation

3. Contrastive Consensus Graph Learning for Multi-View Clustering

4. Detecting $k$-Vertex Cuts in Sparse Networks via a Fast Local Search Approach

5. A Multiobjective Genetic Algorithm to Find Communities in Complex Networks

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