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Parsing as a Cue-Based Retrieval Model.

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  • Author(s): Dotlačil J;Dotlačil J
  • Source:
    Cognitive science [Cogn Sci] 2021 Aug; Vol. 45 (8), pp. e13020.
  • Publication Type:
    Journal Article; Research Support, Non-U.S. Gov't
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Wiley-Blackwell Country of Publication: United States NLM ID: 7708195 Publication Model: Print Cited Medium: Internet ISSN: 1551-6709 (Electronic) Linking ISSN: 03640213 NLM ISO Abbreviation: Cogn Sci Subsets: MEDLINE
    • Publication Information:
      Publication: 2009-: Hoboken, N.J. : Wiley-Blackwell
      Original Publication: Norwood, N. J., Ablex Pub. Corp.
    • Subject Terms:
    • Abstract:
      This paper develops a novel psycholinguistic parser and tests it against experimental and corpus reading data. The parser builds on the recent research into memory structures, which argues that memory retrieval is content-addressable and cue-based. It is shown that the theory of cue-based memory systems can be combined with transition-based parsing to produce a parser that, when combined with the cognitive architecture ACT-R, can model reading and predict online behavioral measures (reading times and regressions). The parser's modeling capacities are tested against self-paced reading experimental data (Grodner & Gibson, 2005), eye-tracking experimental data (Staub, 2011), and a self-paced reading corpus (Futrell et al., 2018).
      (© 2021 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)
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    • Grant Information:
      VC.GW17.112 / 6216 Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)
    • Contributed Indexing:
      Keywords: ACT-R; Computational psycholinguistics; Cue-based retrieval; Memory retrieval; Modeling reading data; Processing
    • Publication Date:
      Date Created: 20210811 Date Completed: 20211004 Latest Revision: 20240403
    • Publication Date:
      20240403
    • Accession Number:
      PMC8459291
    • Accession Number:
      10.1111/cogs.13020
    • Accession Number:
      34379334