• DocumentCode
    2391576
  • Title

    Visual knowledge exploration and discovery from different points of view

  • Author

    Dadzie, Aba-Sah ; Petrelli, Daniela

  • Author_Institution
    Dept. of Inf. Studies, Univ. of Sheffield, Sheffield, UK
  • fYear
    2009
  • fDate
    12-13 Oct. 2009
  • Firstpage
    227
  • Lastpage
    228
  • Abstract
    Complex scenario analysis requires the exploration of multiple hypotheses and supporting evidence for each argument posed. Knowledge-intensive organisations typically analyse large amounts of inter-related, heterogeneous data to retrieve the knowledge this contains and use it to support effective decision-making. We demonstrate the use of interactive graph visualisation to support hierarchical, task-driven, hypothesis investigation. The visual investigative analysis is guided by task and domain ontologies used to capture the structure of the investigation process and the experience gained and knowledge created in previous, related investigations.
  • Keywords
    data mining; data visualisation; decision making; information retrieval; ontologies (artificial intelligence); decision making; domain ontologies; heterogeneous data analysis; interactive graph visualisation; knowledge retrieval; knowledge-intensive organisations; visual knowledge discovery; visual knowledge exploration; Assembly systems; Bicycles; Computer science; Decision making; Failure analysis; Information analysis; Information retrieval; Ontologies; Project management; Visualization; H.5.2 [Information Interfaces and Presentation]: User Interfaces—Graphical user interfaces (GUI); K.6.1 [Management of Computing and Information Systems]: Project and People Management—Life Cycle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology, 2009. VAST 2009. IEEE Symposium on
  • Conference_Location
    Atlantic City, NJ
  • Print_ISBN
    978-1-4244-5283-5
  • Type

    conf

  • DOI
    10.1109/VAST.2009.5333438
  • Filename
    5333438