An anytime-anywhere approach for maximal clique enumeration in social network analysis

Research output: Contribution to journalConference articlepeer-review

Abstract

Social network analysis (SNA) is a set of broadly used techniques designed for analyzing structural information contained in interactions. However, current SNA tools have a poor ability to handle large and dynamic social networks. One particular problem of interest is that of maximal clique enumeration used for studying modularity/community. Critical challenges for this problem include limited scalability and poor ability for handling dynamism. In this paper, we design and implement an anytime anywhere approach for maximal clique enumeration problem in SNA. Through a set of experiments on random graphs, we validate and demonstrate the effectiveness and efficiency of our approach.

Original languageEnglish (US)
Article number4811845
Pages (from-to)3529-3535
Number of pages7
JournalConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
DOIs
StatePublished - Dec 1 2008
Externally publishedYes
Event2008 IEEE International Conference on Systems, Man and Cybernetics, SMC 2008 - Singapore, Singapore
Duration: Oct 12 2008Oct 15 2008

Keywords

  • Anytime anywhere methodologies
  • Maximal clique
  • Social network analysis

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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