Skip to main content

Group Detection

  • Reference work entry
Encyclopedia of Machine Learning
  • 274 Accesses

Synonyms

Community detection; Graph clustering; Modularity detection

Definition

Group detection can defined as the clustering of nodes in a graph into groups or communities. This may be a hard partitioning of the nodes, or may allow for overlapping group memberships. A community can be defined as a group of nodes that share dense connections among each other, while being less tightly connected to nodes in different communities in the network. The importance of communities lies in the fact that they can often be closely related to modular units in the system that have a common function, e.g., groups of individuals interacting with each other in a society (Girvan & Newman, 2002), WWW pages related to similar topics (Flake, Lawrence, Giles, & Coetzee, 2002), or proteins having the same biological function within the cell (Chen & Yuan, 2006).

Motivation and Background

The work done in group detection goes back as early as the 1920s when Stuart Rice clustered data by hand to investigate...

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

Access this chapter

Institutional subscriptions

References

  • Alpert, C., Kahng, A., & Yao, S. (1999). Spectral partitioning: The more eigenvectors, the better. Discrete Applied Mathematics, 90, 3–26.

    Article  MathSciNet  MATH  Google Scholar 

  • Arenas, A., Daz-Guilera, A., & Prez-Vicente, C. J. (2006). Synchronization reveals topological scales in complex networks. Physical Review Letters, 96(11), 114102.

    Article  Google Scholar 

  • Chen, J., & Yuan, B. (2006). Detecting functional modules in the yeast protein–protein interaction network. Bioinformatics, 22(18), 2283–2290.

    Article  Google Scholar 

  • Flake, G. W., Lawrence, S., Giles, C. L., & Coetzee, F. (2002). Self-organization and identification of web communities. IEEE Computer, 35, 66–71.

    Google Scholar 

  • Girvan, M., & Newman, M. E. J. (2002). Community structure in social and biological networks. Proceedings of National Academy of Science, 99, 7821–7826.

    Article  MathSciNet  MATH  Google Scholar 

  • Hartigan, J. A. (1975). Clustering algorithms. New York: Wiley.

    MATH  Google Scholar 

  • Homans, G. C. (1950). The human group. New York: Harcourt, Brace.

    Google Scholar 

  • Lancichinetti, A., Fortunato, S., & Kertesz, J. (2009). Detecting the overlapping and hierarchical community structure in complex networks. New Journal of Physics, 11, 033015.

    Article  Google Scholar 

  • MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of fifth Berkeley symposium on mathematical statistics and probability (Vol. 1, pp. 281–297). Berkeley, CA: University of California Press.

    Google Scholar 

  • Newman, M. E. J. (2004). Fast algorithm for detecting community structure in networks. Physical Review E, 69(6), 066133.

    Article  Google Scholar 

  • Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69, 026113.

    Article  Google Scholar 

  • Palla, G., Dernyi, I., Farkas, I., & Vicsek, T. (2005). Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043), 814–818.

    Article  Google Scholar 

  • Rice, S. A. (1927). The identification of blocs in small political bodies. American Political Science Review, 21, 619–627.

    Article  Google Scholar 

  • Rosvall, M., & Bergstrom, C. T. (2008). Maps of random walks on complex networks reveal community structure. Proceedings of National Academy of Science, 105, 1118–1123.

    Article  Google Scholar 

  • Shalizi, C. R., Camperi, M. F., & Klinkner, K. L. (2007). Discovering functional communities in dynamical networks. Statistical network analysis: Models, issues, and new directions (pp. 140–157). Berlin: Springer-Verlag.

    Google Scholar 

  • Tantipathananandh, C., & Berger-Wolf, T. Y. (2009). Algorithms for identifying dynamic communities. In Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, Paris. New York: ACM.

    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 Science+Business Media, LLC

About this entry

Cite this entry

Sharara, H., Getoor, L. (2011). Group Detection. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_355

Download citation

Publish with us

Policies and ethics