Large-Scale Graph Visualization and Analytics.

Novel approaches to network visualization and analytics use sophisticated metrics that enable rich interactive network views and node grouping and filtering. A survey of graph layout and simplification methods reveals considerable progress in these new directions. The first Web extra at http://youtu...

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Detalles Bibliográficos
Publicado en:Computer (00189162) Vol. 46; no. 7; pp. 39 - 47
Autores principales: Ma, Kwan-Liu, Muelder, Chris W.
Formato: Artículo
Publicado: IEEE Jul2013
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1109/MC.2013.242
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        au:
          Ma, Kwan-Liu
          Muelder, Chris W.
        affil: University of California, Davis
      su:
        Visual analytics
        Data visualization
        Visual programming languages (Computer science)
        Internet
        Methods engineering
      sug:
        subj:
          Visual analytics
          Data visualization
          Visual programming languages (Computer science)
          Internet
          Methods engineering
      keyword:
        big data
        Data handling
        Database systems
        Dynamic networks
        graph visualization
        network analytics
        Social network services
        social networks
      ab: Novel approaches to network visualization and analytics use sophisticated metrics that enable rich interactive network views and node grouping and filtering. A survey of graph layout and simplification methods reveals considerable progress in these new directions. The first Web extra at http://youtu.be/ee8nr9LDHXw is a video segment showing dynamic graph layout results for visualizing evolving Internet connectivity. The global approach meets layout criteria--balanced quality and stability with nodes largely remaining stable, but clusters are compacted. The images are freeze frames of three time steps. The second Web extra at http://youtu.be/oWolTjZMGfo is a video segment showing dynamic graph layout results for visualizing evolving Internet connectivity. The incremental approach uses space efficiently. Motion is slow, smooth, and affine, and so is easy to follow, but quality degrades over time to ensure stable animation.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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