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Elicitation of Knowledge from Multiple Experts Using Network Inference
September-October 1997 (vol. 9 no. 5)
pp. 688-696

Abstract—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.

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Index Terms:
Knowledge acquisition, multiple experts, network inference, quality of rules, influence diagram.
Citation:
Robert Rush, William A. Wallace, "Elicitation of Knowledge from Multiple Experts Using Network Inference," IEEE Transactions on Knowledge and Data Engineering, vol. 9, no. 5, pp. 688-696, Sept.-Oct. 1997, doi:10.1109/69.634748
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