Cart (Loading....) | Create Account
Close category search window
 

Bayesian Network Inference with Qualitative Expert Knowledge for Decision Support Systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jongsawat, N. ; Grad. Sch. of IT in Bus., Siam Univ., Bangkok, Thailand ; Premchaiswadi, W.

In this paper, we consider a methodology that utilizes qualitative expert knowledge for inference in a Bayesian network. The decision-making assumptions and the mathematical equation for Bayesian inference are derived based on data and knowledge obtained from experts. A detailed method to transform knowledge into a set of qualitative statements and an “a priori” distribution for Bayesian probabilistic models are proposed. We also propose a simplified method for constructing the “a prior” model distribution. Each statement obtained from the experts is used to constrain the model space to the subspace which is consistent with the statement provided. Finally, we present qualitative knowledge models and then show a full formalism of how to translate a set of qualitative statements into probability inequality constraints.

Published in:

Software Engineering Artificial Intelligence Networking and Parallel/Distributed Computing (SNPD), 2010 11th ACIS International Conference on

Date of Conference:

9-11 June 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.