• DocumentCode
    2973765
  • Title

    A Bayesian approach to simultaneously quantify assignment and linguistic uncertainty

  • Author

    Chavez, G.M. ; Ross, T.J.

  • Author_Institution
    Los Alamos Nat. Lab., Los Alamos, NM, USA
  • fYear
    2011
  • fDate
    18-20 March 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Subject matter expert assessments can include both assignment and linguistic uncertainty. This paper examines assessments containing linguistic uncertainty associated with a qualitative description of a specific state of interest and the assignment uncertainty associated with assigning the state to a particular qualitative value. A Bayesian approach is examined to simultaneously quantify both assignment and linguistic uncertainty in the posterior probability. The approach is applied to a simplified damage assessment model involving both assignment and linguistic uncertainty. The utility of the approach and the conditions under which the approach is feasible are examined and identified.
  • Keywords
    Bayes methods; computational linguistics; probability; uncertainty handling; Bayesian approach; assignment quantification; assignment uncertainty; damage assessment model; linguistic uncertainty; posterior probability; subject matter expert assessments; Bayesian methods; Equations; Mathematical model; Pragmatics; Risk management; Security; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society (NAFIPS), 2011 Annual Meeting of the North American
  • Conference_Location
    El Paso, TX
  • ISSN
    Pending
  • Print_ISBN
    978-1-61284-968-3
  • Electronic_ISBN
    Pending
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2011.5751911
  • Filename
    5751911