By Topic

Measurement issues in knowledge engineering

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
$33 $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

1 Author(s)
L. Adelman ; Dept. of Inf. Syst. & Syst. Eng., George Mason Univ., Fairfax, VA, USA

There are five sources (or determinants) of knowledge base quality: domain experts, knowledge engineers, knowledge representation schemes, knowledge elicitation methods, and problem domains. The knowledge base for many expert systems is developed for a problem domain using one domain expert, one knowledge engineer, one knowledge representation scheme, and one elicitation method. Since there is minimal research demonstrating that the possible variation in each of these sources does not significantly affect the quality of the knowledge base, the generalizability (or validity) of such systems in real-world settings is questionable. Consequently, research is needed to assess the extent to which system validity is affected by these sources of variability. Toward this end, the results of reanalyzing the data from an experiment varying domain experts, knowledge engineers, and elicitation methods when developing a multiattributed representation scheme for combat readiness are presented. No significant effects were obtained for elicitation method or knowledge engineer

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:19 ,  Issue: 3 )