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EDU-Based Similarity for Paraphrase Identification

  • Ngo Xuan Bach
  • Nguyen Le Minh
  • Akira Shimazu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7934)

Abstract

We propose a new method to compute the similarity between two sentences based on elementary discourse units, EDU-based similarity. Unlike conventional methods, which directly compute similarities based on sentences, our method divides sentences into discourse units and uses them to compute similarities. We also show the relation between paraphrases and discourse units, which plays an important role in paraphrasing. We apply our method to the paraphrase identification task. By using only a single SVM classifier, we achieve 93.1% accuracy on the PAN corpus, a large corpus for detecting paraphrases.

Keywords

Paraphrase Identification Elementary Discourse Unit Text Similarity MT Metrics 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ngo Xuan Bach
    • 1
  • Nguyen Le Minh
    • 1
  • Akira Shimazu
    • 1
  1. 1.School of Information ScienceJapan Advanced Institute of Science and TechnologyNomiJapan

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