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A Review of Community Detection Algorithms Based on Modularity Optimization
Community structure is considered to be one of the most important features of the real network. Community detection helps to understand the real construction of the network and can better analyze various complex systems. In this paper, five algorithms based on module degree optimization (GN, FN, CNM...
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Published in: | Journal of physics. Conference series 2018-08, Vol.1069 (1), p.12123 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Community structure is considered to be one of the most important features of the real network. Community detection helps to understand the real construction of the network and can better analyze various complex systems. In this paper, five algorithms based on module degree optimization (GN, FN, CNM, Louvain, SML) are introduced. The ideas and design principles of this algorithms are introduced in detail, and the characteristics and advantages and disadvantages of each method are summarized. Finally, the prospect of this kind of algorithm is summarized. |
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ISSN: | 1742-6588 1742-6596 |
DOI: | 10.1088/1742-6596/1069/1/012123 |