Text generation: using discourse strategies and focus constraints to generate natural language text
Text generation: using discourse strategies and focus constraints to generate natural language text
Attention, intentions, and the structure of discourse
Computational Linguistics
Generating explanations in context
IUI '93 Proceedings of the 1st international conference on Intelligent user interfaces
Modeling Legal Arguments: Reasoning with Cases and Hypotheticals
Modeling Legal Arguments: Reasoning with Cases and Hypotheticals
Using a Description Classifier to Enhance Knowledge Representation
IEEE Expert: Intelligent Systems and Their Applications
A reactive approach to explanation in expert and advice-giving systems
A reactive approach to explanation in expert and advice-giving systems
Controlling lexical substitution in computer text generation
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Cooking up referring expressions
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Planning text for advisory dialogues
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Verbal Coaching During a Real-Time Task
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
A discourse-aware graph-based content-selection framework
INLG '10 Proceedings of the 6th International Natural Language Generation Conference
Interactive SIGHT: textual access to simple bar charts
The New Review of Hypermedia and Multimedia - Web Accessibility
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A striking difference between the interactions that students have with human tutors and those they have with computer-based instruction system is that human tutors frequently refer to their own previous explanations. Based on a study of human-human instructional interactions, we are categorizing the uses of previous discourse and are developing a computational model of this behavior. In this paper, I describe the strategies we have implemented for identifying relevant prior explanations, and the mechanisms that enable our text planner to exploit the information stored in its discourse history in order to omit information that has previously been communicated, to point out similarities and differences between entities and situations, and to mark re-explanations in circumstances where they are deemed appropriate.