Open Access
Issue
MATEC Web of Conferences
Volume 22, 2015
International Conference on Engineering Technology and Application (ICETA 2015)
Article Number 01056
Number of page(s) 5
Section Information and Communication Technology
DOI https://doi.org/10.1051/matecconf/20152201056
Published online 09 July 2015
  1. Y Bo, L Da-You. & L Jiming, et al. 2009. Complex Network Clustering Algorithms. Journal of Software. 20(1): 54–66. [CrossRef]
  2. Girvan M. & Newman M E J. 2002. Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA. 99(12): 7821–7826. [CrossRef] [MathSciNet] [PubMed]
  3. Chauhan S, Girvan M. & Ott E. 2009. Spectral properties of networks with community structure. Phys. Rev. E., 80(5): 2797–2804. [CrossRef]
  4. Evans T S. & Lambiotte R. 2009. Line graphs, link partitions, and overlapping communities. Phys. Rev. E., 80(1): 106105.
  5. Ball B, Karrer B. & Newman M E J. 2011. An efficient and principled method for detecting communities in networks. Physical Review E., 84(3): 1–14.
  6. G Wen-Yan, H E Nan. & L I De-Yi, et al. 2009. Community Discovery Method in Networks Based on Topological Potential: 20, 2241–2254.
  7. S Lixin. & Z Junxing. 2014. Label propagation algorithm based on potential function for community detection. Journal of Computer Applications. 34(3): 738–741.
  8. Cheng X Q. & Shen H W. 2010. Uncovering the community structure associated with the diffusion dynamics on networks. J. Stat. Mech., P04024.
  9. Zhou H J. 2003. Network landscape from a Brownian particle`s perspective. Phys. Rev. E., 67(4): 041908. [CrossRef]
  10. Q Liu. 2014. Overlapping community detection algorithm based on expansion of gravitational degree. 35(3): 852–856.
  11. Liu Jian-Guo, Ren Zhou-Ming, Guo Qiang. & Wang Bing-Hong. 2013. Node importance ranking of complex networks. Acta Physica Sinica, 62(17): 178901.
  12. Z Zhao, H Yu. & Z Zhu, et al. 2014. Identifying Influential Spreaders Based on Network Community Structure. 37(4): 753–766.
  13. Clauset A, Newman M E J. & Moore C. 2004. Finding community structure in very large networks. Phys. Rev. E,. 70(6): 066111. [CrossRef]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.