Elsevier

Artificial Intelligence

Volume 27, Issue 1, September 1985, Pages 1-41
Artificial Intelligence

Discourse strategies for generating natural-language text☆

https://doi.org/10.1016/0004-3702(85)90082-7Get rights and content

Abstract

If a generation system is to produce text in response to a given communicative goal, it must be able to determine what to include in its text and how to organize this information so that it can be easily understood. In this paper, a computational model of discourse strategies is presented that can be used to guide the generation process in its decisions about what to say next. The model is based on an analysis of naturally occurring texts and represents strategies that can be used for three communicative goals: define, compare, and describe. We show how this model has been implemented in text, a system which generates paragraph-length responses to questions about database structure.

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    • ☆

    This work was done while the author was a graduate student at University of Pennsylvania and was partially supported by NSF grant #MCS81-07290. Research in artificial intelligence at Columbia University is supported by ARPA grant N00039-84-C-0165 and ONR grant N00014-82-K-0256.

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