Tailoring object descriptions to a user's level of expertise
Computational Linguistics - Special issue on user modeling
Generating descriptions that exploit a user's domain knowledge
Current research in natural language generation
OFFICE-PLAN: Tackling the Synthesis-Frontier
GWAI '89 Proceedings of the 13th German Workshop on Artificial Intelligence
Towards Finding The Reasons Behind - Generating The Content Of Explanation
GWAI '91 15. Fachtagung für Künstliche Intelligenz,
A Model for Adapting Explanations to the User‘s Likely Inferences
User Modeling and User-Adapted Interaction
Interpreting and generating indirect answers
Computational Linguistics
Conversational implicatures in indirect replies
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Generating indirect answers to Yes-No questions
INLG '94 Proceedings of the Seventh International Workshop on Natural Language Generation
Content selection and organization as a process involving compromises
INLG '94 Proceedings of the Seventh International Workshop on Natural Language Generation
An optimizing method for structuring inferentially linked discourse
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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This paper presents an approach for achieving conciseness in generating explanations, which is done by exploiting formal reconstructions of aspects of the Gricean principle of relevance to simulate conversational implicature. By applying contextually motivated inference rules in an anticipation feed-back loop, a set of propositions explicitly representing an explanation's content is reduced to a subset which, in the actual context, can still be considered to convey the message adequately.