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Discursive Sentence Compression

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7817)

Abstract

This paper presents a method for automatic summarization by deleting intra-sentence discourse segments. First, each sentence is divided into elementary discourse units and, then, less informative segments are deleted. To analyze the results, we have set up an annotation campaign, thanks to which we have found interesting aspects regarding the elimination of discourse segments as an alternative to sentence compression task. Results show that the degree of disagreement in determining the optimal compressed sentence is high and increases with the complexity of the sentence. However, there is some agreement on the decision to delete discourse segments. The informativeness of each segment is calculated using textual energy, a method that has shown good results in automatic summarization.

Keywords

  • American National Standard Institute
  • Original Sentence
  • Discourse Marker
  • Automatic Summarization
  • Textual Energy

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Molina, A., Torres-Moreno, JM., SanJuan, E., da Cunha, I., Sierra Martínez, G.E. (2013). Discursive Sentence Compression. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2013. Lecture Notes in Computer Science, vol 7817. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37256-8_33

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  • DOI: https://doi.org/10.1007/978-3-642-37256-8_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37255-1

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