Skip to main content

Research of Community Discovery Algorithm Guided by Multimodal Function Optimization

  • Conference paper
Information and Automation (ISIA 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 86))

Included in the following conference series:

  • 1167 Accesses

Abstract

This paper introduces the concept of community seed, comes up with a novel algorithm which based on the multimodal function optimization idea. Generally, the relationship between\\nodes in the same community is much closer than nodes in different communities. We use different sizes of network structures Zachary and Dolphins to test our algorithm, the experimental results show that this method is able to finish dividing the network in low time complexity, high efficiency without any priori information.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Li, X.: Adaptively choosing neighbourhood bests using species in a particle swarm optimizer for multimodal function optimization. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 105–116. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  2. Gan, W.-y., He, N., Li, D.-y.: Community Discovery Method in Networks Based on Topological Potential. J. Journal of Software 20, 2241–2254 (2009)

    Article  Google Scholar 

  3. Zachary, W.W.: An information flow model for conflict and fission in small groups. N. Journal of Anthropological Research 33, 452–473 (1977)

    Article  Google Scholar 

  4. Lusseau, D., Schneider, K., Boisseau, O.J.: The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations—Can geographic isolation explain this unique trait? J. Behavioral Ecology and Sociobiology 54, 396–405 (2003)

    Article  Google Scholar 

  5. Lusseau, D., Newman, M.E.J.: Identifying the role that animals play in their social networks. J. Proc. of the Royal Society B: Biological Sciences 271, 477–481 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Rui-xin, M., Xiao, W. (2011). Research of Community Discovery Algorithm Guided by Multimodal Function Optimization. In: Qi, L. (eds) Information and Automation. ISIA 2010. Communications in Computer and Information Science, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19853-3_100

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19853-3_100

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19852-6

  • Online ISBN: 978-3-642-19853-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics