| CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY |
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A New Definition of Modularity for Community Detection in Complex Networks |
| YE Zhen-Qing1,2, ZHANG Ke3, HU Song-Nian1, YU Jun1,2** |
1James D. Watson Institute of Genome Sciences, College of Life Sciences, Zhejiang University, Hangzhou 310058
2CAS Key Laboratory of Genome Sciences and Information, Beijing Institute Genomics, Chinese Academy of Sciences, Beijing 100029
3Medical Systems Biology Research Center, Tsinghua University School of Medicine, Beijing 100084 |
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| Cite this article: |
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YE Zhen-Qing, ZHANG Ke, HU Song-Nian et al 2012 Chin. Phys. Lett. 29 098901 |
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Abstract We propose a new definition of modularity, i.e. the Qd function, for network analysis, which takes the edge density and topological structure of modules into account and is different from the original strategy of simply calculating the number of edges (the definition of modularity Q introduced by Newman and Girvan). Armed with this novel quality function Qd, we implement an adaptive clustering algorithm for process optimization, and apply our strategy to several synthetic and real-world networks. The results of our exercises demonstrate a better performance in extracting accurate community ingredients from complex networks.
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Received: 18 November 2011
Published: 01 October 2012
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| PACS: |
89.75.Hc
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(Networks and genealogical trees)
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02.10.Ox
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(Combinatorics; graph theory)
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