By Topic

Toward an art and science of knowledge engineering: a case for belief networks

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)
Abramson, B. ; Univ. of Southern California, Los Angeles, CA, USA ; Ng, K.-C.

The knowledge engineering of belief networks is discussed. Several design issues that arose during the construction of two belief network-based systems, Pathfinder and ARCO1, are described. The issues of accuracy, consistency, and calibration as they emerged during the design of these systems are addressed, and the ways in which compatibility of all networks designed for the same domain suggests an architecture for combining the recommendations of independently designed knowledge bases into a single, consensus recommendation are discussed

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:5 ,  Issue: 4 )