an efficient hierarchy algorithm for community detection in complex networks

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ID: 131575
2014
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Abstract
Community structure is one of the most fundamental and important topology characteristics of complex networks. The research on community structure has wide applications and is very important for analyzing the topology structure, understanding the functions, finding the hidden properties, and forecasting the time-varying of the networks. This paper analyzes some related algorithms and proposes a new algorithm—CN agglomerative algorithm based on graph theory and the local connectedness of network to find communities in network. We show this algorithm is distributed and polynomial; meanwhile the simulations show it is accurate and fine-grained. Furthermore, we modify this algorithm to get one modified CN algorithm and apply it to dynamic complex networks, and the simulations also verify that the modified CN algorithm has high accuracy too.
Reference Key
zhang2014mathematicalan Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Lili Zhang;Qing Ye;Yehong Shao;Chenming Li;Hongmin Gao
Journal journal of power sources
Year 2014
DOI
10.1155/2014/874217
URL
http://dx.doi.org/10.1155/2014/874217
Keywords
civil engineering (general)mathematics engineering (general)

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