Community Detection Based on Surrogate Network
- Publisher:
- Springer Nature
- Publication Type:
- Conference Proceeding
- Citation:
- Communications in Computer and Information Science, 2022, 1566 CCIS, pp. 45-53
- Issue Date:
- 2022-01-01
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Community Detection Based on Surrogate Network.pdf | Published version | 62.45 MB |
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This paper presents a novel methodology to detect communities in complex networks based on evolutionary computation. In the proposed method, a surrogate network with a more detectable community structure than the original network is firstly constructed based on the eigenmatrix of the adjacent matrix. Then the community partition can be found by successively optimizing the modularity of the surrogate network and the original network with an evolutionary algorithm. The proposed method is tested on both synthetic and real-world networks and compared with some existing algorithms. Experimental results show that employing the constructed surrogate networks can effectively improve the community detection efficiency.
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