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Mathematical Problems in Engineering
Volume 2014, Article ID 874217, 12 pages
Research Article

An Efficient Hierarchy Algorithm for Community Detection in Complex Networks

1College of Computer and Information Engineering, Hohai University, Nanjing 211100, China
2Arts and Science, Ohio University Southern, Ironton, OH, USA

Received 31 March 2014; Revised 19 July 2014; Accepted 14 September 2014; Published 23 October 2014

Academic Editor: Ren-Jieh Kuo

Copyright © 2014 Lili Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.