• DocumentCode
    119610
  • Title

    Event-based text visual analytics

  • Author

    Wang, Ji ; Bradel, Lauren ; North, Chris

  • Author_Institution
    Virginia Tech
  • fYear
    2014
  • fDate
    25-31 Oct. 2014
  • Firstpage
    333
  • Lastpage
    334
  • Abstract
    We present an event-based approach for solving a directed sensemaking task in which we combine powerful information foraging tools with intuitive synthesis spaces to solve the VAST Challenge 2014 Mini-Challenge 1. A combination of student-created and commericially available software are used to solve various aspects of the scenario. In addition to applying entitiy extraction and topic modelling, we enable the user to explore a large dataset using multi-model semantic interaction, which infers analytical reasoning from user actions to augment the data spatialization and determine what information should be presented and suggested to the user. Additionally, we visualize extracted topics using Tableau to construct a timeline of events surrounding the questions posed by the challenge.
  • Keywords
    Sensemaking; event extraction; semantic interaction; topic modelling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on
  • Conference_Location
    Paris, France
  • Type

    conf

  • DOI
    10.1109/VAST.2014.7042552
  • Filename
    7042552