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A Study of Abstractive Summarization Using Semantic Representations and Discourse Level Information

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Text, Speech, and Dialogue (TSD 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10415))

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Abstract

The present work proposes an exploratory study of abstractive summarization integrating semantic analysis and discursive information. Firstly, we built a conceptual graph using some lexical resources and Abstract Meaning Representation (AMR). Secondly, we applied PageRank algorithm to get the most relevant concepts. Also, we incorporated discursive information of Rethorical Structure Theory (RST) into the PageRank to improve the relevant concepts identification. Finally, we made some rules over the relevant concepts and applied SimpleNLG to make the summaries. This study was performed on the corpus of DUC 2002 and the results showed a F1-measure of 24% in Rouge-1 when AMR and RST were used, proving their usefulness in this task.

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Notes

  1. 1.

    Available at https://nlp.stanford.edu/software/. Accessed on February 2017.

  2. 2.

    Available at http://alt.qcri.org/semeval2016/. Accessed in February 2017.

  3. 3.

    Proposition Bank Available at https://verbs.colorado.edu/mpalmer/projects/ace.html. Accessed on March 2017.

  4. 4.

    Elementary Discourse Unit is the basic unit in discourse-level.

  5. 5.

    https://github.com/simplenlg/simplenlg. Last visited in February 2017.

  6. 6.

    http://duc.nist.gov/data.html. Last visited in February 2017.

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Author information

Authors and Affiliations

  1. Escuela de Posgrado, Maestría en Informática, Pontificia Universidad Católica del Perú, Lima, Perú

    Gregory César Valderrama Vilca

  2. Grupo de Reconocimiento de Patrones e Inteligencia Artificial Aplicada, Departamento de Ingeniería, Pontificia Universidad Católica del Perú, Lima, Perú

    Marco Antonio Sobrevilla Cabezudo

Authors
  1. Gregory César Valderrama Vilca
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  2. Marco Antonio Sobrevilla Cabezudo
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Correspondence to Marco Antonio Sobrevilla Cabezudo .

Editor information

Editors and Affiliations

  1. University of West Bohemia, Pilsen, Czech Republic

    Kamil Ekštein

  2. University of West Bohemia, Pilsen, Czech Republic

    Václav Matoušek

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Vilca, G.C.V., Cabezudo, M.A.S. (2017). A Study of Abstractive Summarization Using Semantic Representations and Discourse Level Information. In: Ekštein, K., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science(), vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_54

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  • DOI: https://doi.org/10.1007/978-3-319-64206-2_54

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-64206-2

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