ono1994abstract Abstract Generation Based On Rhetorical Structure Extraction

Ono, K., Sumita, K., and Miike, S. (1994). Abstract generation based on rhetorical structure extraction. In Proceedings of Coling '94, pages 344-348, Morristown, NJ, USA.



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[das2007survey]

Deep Natural Language Analysis Methods
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Ono et al. (1994) put forward a computational model of discourse for Japanese expository writings, where they elaborate a practical procedure for extracting the discourse rhetorical structure, a binary tree representing relations between chunks of sentences (rhetorical structure trees are used more intensively in (Marcu, 1998a), as we will see below). This structure was extracted using a series of NLP steps: sentence analysis, rhetorical relation extraction, segmentation, candidate generation and preference judgement. Evaluation was based on the relative importance of rhetorical relations. In the following step, the nodes of the rhetorical structure tree were pruned to reduce the sentence, keeping its important parts. Same was done for paragraphs to nally produce the summary. Evaluation was done with respect to sentence coverage and 30 editorial articles of a Japanese newspaper were used as the dataset. The articles had corresponding sets of key sentences and most important key sentences judged by human subjects. The key sentence coverage was about 51% and the most important key sentence coverage was 74%, indicating encouraging results.
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