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
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;
Conference_Titel :
Fuzzy Information Processing Society (NAFIPS), 2011 Annual Meeting of the North American
Conference_Location :
El Paso, TX
Print_ISBN :
978-1-61284-968-3
Electronic_ISBN :
Pending
DOI :
10.1109/NAFIPS.2011.5751911