• DocumentCode
    1816325
  • Title

    Measuring the quality of network visualization

  • Author

    Chen, Chaomei

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Drexel Univ., Philadelphia, PA
  • fYear
    2005
  • fDate
    7-11 June 2005
  • Firstpage
    405
  • Lastpage
    405
  • Abstract
    A quantitative method is developed for measuring the quality of network visualizations in terms of log-likelihood metrics resulted from expectation maximization (EM) clustering intrinsic and extrinsic attributes of network nodes
  • Keywords
    data visualisation; learning (artificial intelligence); pattern clustering; expectation maximization clustering; log-likelihood metrics; network nodes; network visualizations; quality measurement; Chaos; Clustering algorithms; Data visualization; Educational institutions; Graphical user interfaces; Information science; Information systems; Machine learning; Machine learning algorithms; User interfaces; EM clustering; network visualization; quality metrics of quality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Libraries, 2005. JCDL '05. Proceedings of the 5th ACM/IEEE-CS Joint Conference on
  • Conference_Location
    Denver, CO
  • Print_ISBN
    1-58113-876-8
  • Type

    conf

  • DOI
    10.1145/1065385.1065509
  • Filename
    4118608
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1816325