• DocumentCode
    22477
  • Title

    Spectrum-Based Network Visualization for Topology Analysis

  • Author

    Xianlin Hu ; Aidong Lu ; Xintao Wu

  • Author_Institution
    Univ. of North Carolina at Charlotte, Charlotte, NC, USA
  • Volume
    33
  • Issue
    1
  • fYear
    2013
  • fDate
    Jan.-Feb. 2013
  • Firstpage
    58
  • Lastpage
    68
  • Abstract
    Network visualization techniques have been widely used to explore social networks, which are crucial to many application domains. A proposed visual-analytics approach provides functions that were previously hard to obtain. Based on recent achievements in spectrum-based analysis, it uses the features of node distribution and coordinates in the high-dimensional spectral space. Specifically, three-stage node projection and dispersion on a k-dimensional sphere in the spectral space determines the network layout. To assist interactive exploration of network topologies, network visualization and interactive analysis let users filter nodes and edges in a way that´s meaningful to the global topology structure.
  • Keywords
    data analysis; data visualisation; graph theory; social networking (online); filter node; global topology structure; high-dimensional spectral space; k-dimensional sphere; network layout; node coordination; node distribution; social network; spectrum-based analysis; spectrum-based network visualization; three-stage node dispersion; three-stage node projection; topology analysis; visual-analytics approach; Algorithm design and analysis; Data visualization; Dispersion; Layout; Network topology; Social network services; Topology; Visual analytics; Visualization; Algorithm design and analysis; Data visualization; Dispersion; Layout; Network topology; Social network services; Topology; Visual analytics; Visualization; computer graphics; network topology; network visualization; spectrum-based analysis; visual analytics;
  • fLanguage
    English
  • Journal_Title
    Computer Graphics and Applications, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1716
  • Type

    jour

  • DOI
    10.1109/MCG.2012.89
  • Filename
    6231611