Expertise transfer for expert system design
Expertise transfer for expert system design
Operations Research
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ACM SIGART Bulletin - Special issue on knowledge acquisition
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CSCW '90 Proceedings of the 1990 ACM conference on Computer-supported cooperative work
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EKAW'92 Proceedings of the 6th European knowledge acquisition workshop on Current developments in knowledge acquisition
Accountability and computer decision systems
Communications of the ACM
Decision Support Systems - Special issue: DSS on model formulation
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IEEE Transactions on Knowledge and Data Engineering
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IEEE Expert: Intelligent Systems and Their Applications
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IEEE Transactions on Knowledge and Data Engineering
Modeling Relationships among Multiple Graphical Structures
Computational & Mathematical Organization Theory
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Strategic decision making on group collaboration under temporary constraints
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Trigger to Switch Individual's Interest Toward Unconscious Preference
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
LawTech '07 Proceedings of the Fifth IASTED International Conference on Law and Technology
A computing theory for collaborative and transparent decision making under time constraint
Information Systems Frontiers
Process mining by measuring process block similarity
BPM'06 Proceedings of the 2006 international conference on Business Process Management Workshops
Journal of Management Information Systems
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Eliciting knowledge from multiple experts usually entails the use of groups, and thus is subject to the problems inherent in group dynamics. We present a technique for multiple expert knowledge acquisition that does not rely upon the use of groups and can take advantage of technological advances in communications and computing, i.e., the Internet. The approach uses influence diagrams to represent the individual expert's understanding of the problem situation and develops a Multiple Expert Influence Diagram (MEID), a composite representation of the experts' knowledge. Following a review of present methods for multiple expert knowledge elicitation, we formally define the MEID, describe its manner of construction, and discuss its interpretation. We continue with a review of the issues to be faced in implementation of the technique, and give an illustrative example. Finally, we emphasize the need to provide users of decision aids with defensible measures of the quality of the rules produced by these aids. The MEID-approach is intended to serve as a first step in this direction.