A new evolutionary multi-objective community mining algorithm for signed networks
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(6)
Publication Date
Thu Dec 01 2016
Journal Name
Swarm And Evolutionary Computation
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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
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Publication Date
Thu Jan 01 2026
Journal Name
Computers, Materials & Continua
Multi-Objective Evolutionary Framework for High-Precision Community Detection in Complex Networks
Multi-objective optimization
evolutionary algorithms
community detection
heuristic
metaheuristic
hybrid
social network
models
Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can.Therefore,we utilized two objective
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(1)
Publication Date
Mon Oct 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
<b>Enhanced Multi-Objective Evolutionary Algorithm for Community Detection Using a Community Strength-Based Mutation Strategy</b>
Multi-objective optimization
Evolutionary algorithms
Community detection
Metaheuristic
Hybrid
Social network.
Community structures are fundamental in understanding the structure and functionality of complex networks. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of community detection. Recently, multi-objective evolutionary algorithms (MOEAs) have attracted many researchers to identify communities in static networks. Many algorithms have been proposed to find a solution that achieves a trade-off between exploring new areas of the solution space and improving the quality of existing solutions. In this trade-off is crucial; whereas exploitation improves existing solutions, it may fail to find better solutions from insufficiently explored regions o
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Publication Date
Wed Nov 17 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
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(2)
Publication Date
Sun Mar 01 2020
Journal Name
Computer Networks
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(5)
Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
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(46)
Publication Date
Mon Feb 01 2016
Journal Name
Swarm And Evolutionary Computation
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Publication Date
Sat Sep 27 2014
Journal Name
Soft Computing
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(23)
Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Theoretical And Applied Information Technology
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