Detecting community structure in networks by representative energy |
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Authors: | Ji Liu and Guishi Deng |
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Affiliation: | (1) Institute of System Engineering, Dalian University of Technology, Dalian, 116023, China;(2) College of Statistics and Information, Xinjiang University of Finance and Economics, Urumqi, 830012, China |
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Abstract: | Network community has attractedmuch attention recently, but the accuracy and efficiency in finding a community structure is
limited by the lower resolution of modularity. This paper presents a new method of detecting community based on representative
energy. The method can divide the communities and find the representative of community simultaneously. The communities of
network emerges during competing for the representative among nodes in network, thus we can sketch structure of the whole
network. Without the optimizing by modularity, the community of network emerges with competing for representative among those
nodes. To obtain the proximate relationships among nodes, we map the nodes into a spectral matrix. Then the top eigenvectors
are weighted according to their contributions to find the representative node of a community. Experimental results show that
the method is effective in detecting communities of networks. |
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Keywords: | network community community detection representative energy spectral analysis weighted eigenvector |
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