Modeling the user in natural language systems
Computational Linguistics - Special issue on user modeling
Tailoring object descriptions to a user's level of expertise
Computational Linguistics - Special issue on user modeling
Description strategies for naive and expert users
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Prolog/Exl, an inference engine which explains both yes and no answers
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
Tailoring explanations for the user
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
Combining discourse strategies to generate descriptions to users along a naive/expert spectrum
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
User modeling and user interfaces
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
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This paper reports on experiments designed to identify and implement mechanisms for enhancing the explanation capabilities of reasoning programs for medical consultation. The goals of an explanation system are discussed, as is the additional knowledge needed to meet these goals in a medical domain. We have focussed on the generation of explanations that are appropriate for different types of system users. This task requires a knowledge of what is complex and what is important; it is further strengthened by a classification of the associations or causal mechanisms inherent in the inference rules. A causal representation can also be used to aid in refining a comprehensive knowledge base so that the reasoning and explanations are more adequate. We describe a prototype system which reasons from causal inference rules and generates explanations that are appropriate for the user.