A new community detection algorithm based on makov-chains and a team formation model

Patrick J. McSweeney, Kishan Mehrotra, Jae C. Oh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Detecting community structure in complex networks is an active area of research that locates dense regions of connections in networks. We suggest a novel algorithm for community detection using a new node-node association metric (based on Markov-Chains) and a team formation model.

Original languageEnglish (US)
Title of host publicationProceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009
Pages371-372
Number of pages2
DOIs
StatePublished - Oct 15 2009
Event2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009 - Athens, Greece
Duration: Jul 20 2009Jul 22 2009

Publication series

NameProceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009

Other

Other2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009
CountryGreece
CityAthens
Period7/20/097/22/09

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Software
  • Social Sciences(all)

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    McSweeney, P. J., Mehrotra, K., & Oh, J. C. (2009). A new community detection algorithm based on makov-chains and a team formation model. In Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009 (pp. 371-372). (Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009). https://doi.org/10.1109/ASONAM.2009.57