Discourse-driven argument mining in scientific abstracts

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  • dc.contributor.author Accuosto, Pablo
  • dc.contributor.author Saggion, Horacio
  • dc.date.accessioned 2019-07-02T10:58:49Z
  • dc.date.available 2019-07-02T10:58:49Z
  • dc.date.issued 2019
  • dc.description Comunicació presentada a: 24th International Conference on Applications of Natural Language to Information Systems (NLDB), celebrat del 26 al 28 de juny de 2019 a Salford, Regne Unit.
  • dc.description.abstract Argument mining consists in the automatic identification of argumentative structures in texts. In this work we address the open question of whether discourse-level annotations can contribute to facilitate the identification of argumentative components and relations in scientific literature. We conduct a pilot study by enriching a corpus of computational linguistics abstracts that contains discourse annotations with a new argumentative annotation level. The results obtained from preliminary experiments confirm the potential value of the proposed approach.
  • dc.description.sponsorship This work is (partly) supported by the Spanish Government under the María de Maeztu Units of Excellence Programme (MDM-2015-0502).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Accuosto P, Saggion H. Discourse-driven argument mining in scientific abstracts. In: Métais E, Meziane F, Vadera S, Sugumaran V, Saraee M, editors. Natural Language Processing and Information Systems. 24th International Conference on Applications of Natural Language to Information Systems; 2019 Jun 26-28; Salford, UK. Heidelberg: Springer; 2019. p. 182-94. (LNCS, no. 11608). DOI: 10.1007/978-3-030-23281-8_15
  • dc.identifier.doi http://dx.doi.org/10.1007/978-3-030-23281-8_15
  • dc.identifier.isbn 978-3-030-23280-1
  • dc.identifier.uri http://hdl.handle.net/10230/41907
  • dc.language.iso eng
  • dc.publisher Springer
  • dc.relation.ispartof Métais E, Meziane F, Vadera S, Sugumaran V, Saraee M, editors. Natural Language Processing and Information Systems. 24th International Conference on Applications of Natural Language to Information Systems; 2019 Jun 26-28; Salford, UK. Heidelberg: Springer; 2019. p. 182-94. (LNCS, no. 11608).
  • dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-030-23281-8_15
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.subject.keyword Argument mining
  • dc.subject.keyword RST
  • dc.subject.keyword Scientific corpus
  • dc.title Discourse-driven argument mining in scientific abstracts
  • dc.type info:eu-repo/semantics/conferenceObject
  • dc.type.version info:eu-repo/semantics/acceptedVersion

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Congressos (Departament de Tecnologies de la Informació i les Comunicacions)