Visualizing graphs and clusters as maps

Yifan Hu, Emden R. Gansner, Stephen G Kobourov

Research output: Contribution to journalArticle

40 Citations (Scopus)

Abstract

Information visualization is essential in making sense of large datasets. Often, high-dimensional data are visualized as a collection of points in 2D space through dimensionality reduction techniques. However, these traditional methods often don't capture the underlying structural information, clustering, and neighborhoods well. GMap is a practical algorithmic framework for visualizing relational data with geographic-like maps. This approach is effective in various domains.

Original languageEnglish (US)
Article number5567116
Pages (from-to)54-66
Number of pages13
JournalIEEE Computer Graphics and Applications
Volume30
Issue number6
DOIs
StatePublished - 2010

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Keywords

  • clustering
  • computer graphics
  • graph coloring
  • graph drawing
  • graphics and multimedia
  • information visualization
  • maps
  • set visualization

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Visualizing graphs and clusters as maps. / Hu, Yifan; Gansner, Emden R.; Kobourov, Stephen G.

In: IEEE Computer Graphics and Applications, Vol. 30, No. 6, 5567116, 2010, p. 54-66.

Research output: Contribution to journalArticle

Hu, Yifan ; Gansner, Emden R. ; Kobourov, Stephen G. / Visualizing graphs and clusters as maps. In: IEEE Computer Graphics and Applications. 2010 ; Vol. 30, No. 6. pp. 54-66.
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