• DocumentCode
    2422350
  • Title

    OmniSeer: A Cognitive Framework for User Modeling, Reuse of Prior and Tacit Knowledge, and Collaborative Knowledge Services

  • Author

    Cheng, James ; Emami, Roozbeh ; Kerschberg, L. ; Qunhua Zhao ; Hien Nguyen ; Hua Wang ; Huhns, Michael N. ; Valtorta, M. ; Dang, Jian ; Jingshan Huang ; Xi, Suping

  • Author_Institution
    Global InfoTek
  • fYear
    2005
  • fDate
    03-06 Jan. 2005
  • Abstract
    This paper describes the current state of the OmniSeer system. OmniSeer supports intelligence analysts in the handling of massive amounts of data, the construction of scenarios, and the management of hypotheses. OmniSeer models analysts with dynamic user models that capture an analyst´s context, interests, and preferences, thus enabling more efficient and effective information retrieval. OmniSeer explicitly represents the prior and tacit knowledge of analysts, thus enabling transfer and reuse of such knowledge. Both the user and cognitive models employ a Bayesian network fragment representation, which supports principled probabilistic reasoning and analysis. An independent evaluation of OmniSeer was carried out at NIST and will be used to guide further development.
  • Keywords
    Bayesian methods; Collaboration; Context modeling; Data analysis; Information analysis; Information retrieval; Intelligent agent; Intelligent systems; Knowledge management; NIST;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Sciences, 2005. HICSS '05. Proceedings of the 38th Annual Hawaii International Conference on
  • ISSN
    1530-1605
  • Print_ISBN
    0-7695-2268-8
  • Type

    conf

  • DOI
    10.1109/HICSS.2005.462
  • Filename
    1385842