| CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY |
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A Micro-Community Structure Merging Model Using a Community Sample Matrix |
| LI Lin1**, PENG Hao1, LU Song-Nian1, TIAN Ying2 |
1Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240
2Key Laboratory of Materials for High Power Laser, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800
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| Cite this article: |
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LI Lin, PENG Hao, LU Song-Nian et al 2013 Chin. Phys. Lett. 30 018901 |
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Abstract Detecting an overlapping and hierarchical community structure can give a significant insight into structural and functional properties in complex networks. We propose a micro-community structure merging model to detect overlapping and hierarchical communities. The algorithm maps communities to random variables using the community sample matrix to evaluate similarity between communities. After finding density-based micro-community structures, the algorithm merges these reasonable micro-communities iteratively to form communities. Simulation results in three real networks show that the proposed algorithm is more accurate than some existing mechanisms. In this way, we can obtain a detailed understanding of the overlapping and hierarchical communities.
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Received: 02 July 2012
Published: 04 March 2013
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| PACS: |
89.75.Fb
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(Structures and organization in complex systems)
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89.20.Ff
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(Computer science and technology)
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89.20.Hh
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(World Wide Web, Internet)
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89.75.Hc
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(Networks and genealogical trees)
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