Dynamically improving explanations: A revision-based approach to explanation generation (1997)
| Venue: | In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence |
| Citations: | 22 - 4 self |
BibTeX
@INPROCEEDINGS{Callaway97dynamicallyimproving,
author = {Charles B. Callaway},
title = {Dynamically improving explanations: A revision-based approach to explanation generation},
booktitle = {In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence},
year = {1997},
pages = {952--958}
}
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Abstract
Recent years have witnessed rapid progress in explanation generation. Despite these advances, the quality of prose produced by explanation generators warrants significant improvement. Revision-based explanation generation offers a promising means for improving explanations at runtime. In contrast to singledraft explanation generation architectures, a revision-based generator could dynamically create, evaluate, and refine multiple drafts of explanations. However, because of the inherent complexity of revision, previous multisentential revision-based approaches have not scaled up. We have developed a scalable revision-based model of explanation generation that dynamically improves multi-sentential explanations. By operating on abstract discourse plans encoded in a minimalist representation, it combats both the conceptual complexities and the efficiency problems posed by revision. This approach has been implemented in REVISOR, a unification-based revision system. Evaluations of REVISOR'S performance in generating a corpus of extended multi-sentential scientific explanations yielded encouraging results. 1
