Journal of Natural Language Processing
Online ISSN : 2185-8314
Print ISSN : 1340-7619
ISSN-L : 1340-7619
Summarizing a Document by Trimming a Nested Tree Structure
Yuta KikuchiTsutomu HiraoHiroya TakamuraManabu OkumuraMasaaki Nagata
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2015 Volume 22 Issue 3 Pages 197-217


Many methods of text summarization that have recently been proposed combine sentence selection and sentence compression. Although the dependency between words has been used in most of these methods, the dependency between sentences, i.e., the rhetorical structure, has not been exploited in such joint methods. We use both the dependency between words and the dependency between sentences by constructing a nested tree, in which nodes in a document tree representing the dependency between sentences were replaced by a sentence tree representing the dependency between words. We formulate a summarization task as a combinatorial optimization problem, in which the nested tree is trimmed without losing important content in the source document. The results from an empirical evaluation revealed that our method based on the trimming of the nested tree significantly improved the performance of text summarization.

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© 2015 The Association for Natural Language Processing
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