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Multi-level Graph Drawing Using Infomap Clustering

  • Seok-Hee HongEmail author
  • Peter Eades
  • Marnijati Torkel
  • Ziyang Wang
  • David Chae
  • Sungpack Hong
  • Daniel Langerenken
  • Hassan Chafi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11904)

Abstract

Infomap clustering finds the community structures that minimize the expected description length of a random walk trajectory; algorithms for infomap clustering run fast in practice for large graphs. In this paper we leverage the effectiveness of Infomap clustering combined with the multi-level graph drawing paradigm. Experiments show that our new Infomap based multi-level algorithm produces good visualization of large and complex networks, with significant improvement in quality metrics.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Seok-Hee Hong
    • 1
    Email author
  • Peter Eades
    • 1
  • Marnijati Torkel
    • 1
  • Ziyang Wang
    • 1
  • David Chae
    • 1
  • Sungpack Hong
    • 2
  • Daniel Langerenken
    • 2
  • Hassan Chafi
    • 2
  1. 1.University of SydneySydneyAustralia
  2. 2.Oracle Research LabBelmontUSA

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