CSIM: A Fast Community Detection Algorithm Based on Structure Information Maximization

Community detection has been a subject of extensive research due to its broad applications across social media, computer science, biology, and complex systems. Modularity stands out as a predominant metric guiding community detection, with numerous algorithms aimed at maximizing modularity. However,...

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Veröffentlicht in:Electronics (Basel) Jg. 13; H. 6; S. 1119
Hauptverfasser: Liu, Yiwei, Liu, Wencong, Tang, Xiangyun, Yin, Hao, Yin, Peng, Xu, Xin, Wang, Yanbin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.03.2024
Schlagworte:
Algorithms
Complex systems
Complexity
Computer science
Entropy
Greedy algorithms
Mathematical programming
Maximization
Modularity
Optimization
Social networks
China
ISSN:2079-9292, 2079-9292
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Zusammenfassung:Community detection has been a subject of extensive research due to its broad applications across social media, computer science, biology, and complex systems. Modularity stands out as a predominant metric guiding community detection, with numerous algorithms aimed at maximizing modularity. However, modularity encounters a resolution limit problem when identifying small community structures. To tackle this challenge, this paper presents a novel approach by defining community structure information from the perspective of encoding edge information. This pioneering definition lays the foundation for the proposed fast community detection algorithm CSIM, boasting an average time complexity of only O(nlogn). Experimental results showcase that communities identified via the CSIM algorithm across various graph data types closely resemble ground truth community structures compared to those revealed via modularity-based algorithms. Furthermore, CSIM not only boasts lower time complexity than greedy algorithms optimizing community structure information but also achieves superior optimization results. Notably, in cyclic network graphs, CSIM surpasses modularity-based algorithms in effectively addressing the resolution limit problem.
Bibliographie:ObjectType-Article-1
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ISSN:2079-9292
2079-9292
DOI:10.3390/electronics13061119