Uncertainty in Artificial Intelligence
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A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application
Ann Nicholson, Tal Boneh, Tim Wilkin, Kaye Stacey, Liz Sonenberg, Vicki Steinle
Abstract:
Most successful Bayesian network (BN) applications to datehave been built through knowledge elicitation from experts.This is difficult and time consuming, which has lead to recentinterest in automated methods for learning BNs from data. We present a case study in the construction of a BN in anintelligent tutoring application, specifically decimal misconceptions. Wedescribe the BN construction using expert elicitation and then investigate how certainexisting automated knowledge discovery methods might support the BN knowledge engineering process.
Keywords:
Pages: 386-394
PS Link:
PDF Link: /papers/01/p386-nicholson.pdf
BibTex:
@INPROCEEDINGS{Nicholson01,
AUTHOR = "Ann Nicholson and Tal Boneh and Tim Wilkin and Kaye Stacey and Liz Sonenberg and Vicki Steinle",
TITLE = "A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application",
BOOKTITLE = "Proceedings of the Seventeenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-01)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2001",
PAGES = "386--394"
}


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