• DocumentCode
    3262154
  • Title

    Visualizing community centric network layouts

  • Author

    Fagnan, Justin ; Zaïane, Osmar ; Goebel, Randy

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
  • fYear
    2012
  • fDate
    11-13 July 2012
  • Firstpage
    321
  • Lastpage
    330
  • Abstract
    We present our COMmunity Boundary (COMB) and COMmunity Circles (COMC) network layout algorithms that focus on revealing the structure of discovered communities and the relationships between these communities. We believe this information is vital when developing new community mining algorithms as it allows the viewer to more quickly assess the quality of a mining result without appealing to large tables of statistics. To implement our algorithms we have introduced numerous modifications to the existing Fruchterman-Reingold layout, including support for multi-sized vertices, removal of the bounding frame, introduction of circular bounding boxes, and a novel slotting system. Our evaluation argues that both COMB and COMC outperform existing alternatives in their ability to reveal community structure and emphasize inter-community relations.
  • Keywords
    data mining; data visualisation; network theory (graphs); COMB; COMC; Fruchterman-Reingold layout; bounding frame removal; circular bounding boxes; community boundary network layout algorithms; community centric network layout visualization; community circles network layout algorithms; community mining algorithms; multisized vertices; slotting system; Communities; Feeds; Force; Inference algorithms; Layout; Proteins; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Visualisation (IV), 2012 16th International Conference on
  • Conference_Location
    Montpellier
  • ISSN
    1550-6037
  • Print_ISBN
    978-1-4673-2260-7
  • Type

    conf

  • DOI
    10.1109/IV.2012.61
  • Filename
    6295833