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Discourse Element Identification in Student Essays based on Global and Local Cohesion

Wei Song,Ruiji Fu,Lizhen Liu,Ting Liu

Published 2015 in Conference on Empirical Methods in Natural Language Processing

ABSTRACT

We present a method of using cohesion to improve discourse element identification for sentences in student essays. New features for each sentence are derived by considering its relations to global and local cohesion, which are created by means of cohesive resources and subtopic coverage. In our experiments, we obtain significant improvements on identifying all discourse elements, especially of +5% F1 score on thesis and main idea. The analysis shows that global cohesion can better capturethesis statements.

PUBLICATION RECORD

  • Publication year

    2015

  • Venue

    Conference on Empirical Methods in Natural Language Processing

  • Publication date

    2015-09-01

  • Fields of study

    Linguistics, Computer Science

  • Identifiers
    DOI 10.18653/v1/D15-1270
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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