Modeling the scholars: Detecting intertextuality through enhanced word-level n-gram matching.

The study of intertextuality, or how authors make artistic use of other texts in their works, has a long tradition, and has in recent years benefited from a variety of applications of digital methods. This article describes an approach for detecting the sorts of intertexts that literary scholars hav...

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Publicado en:Digital Scholarship in the Humanities Vol. 30; no. 4; pp. 503 - 516
Autores principales: Forstall, Christopher, Coffee, Neil, Buck, Thomas, Roache, Katherine, Jacobson, Sarah
Formato: Artículo
Publicado: Oxford University Press / USA Dec2015
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          Forstall, Christopher
          Coffee, Neil
          Buck, Thomas
          Roache, Katherine
          Jacobson, Sarah
        affil: Department of Classics, University at Buffalo, SUNY, Buffalo, NY, USA
      su:
        Intertextuality
        Epic poetry
        Latin language
        Parallelism (Linguistics)
        Lamma language
      sug:
        subj:
          Intertextuality
          Epic poetry
          Latin language
          Parallelism (Linguistics)
          Lamma language
      ab: The study of intertextuality, or how authors make artistic use of other texts in their works, has a long tradition, and has in recent years benefited from a variety of applications of digital methods. This article describes an approach for detecting the sorts of intertexts that literary scholars have found most meaningful, as embodied in the free Tesserae website http://tesserae.caset.buffalo.edu/. Tests of Tesserae Versions 1 and 2 showed that word-level n-gram matching could recall a majority of parallels identified by scholarly commentators in a benchmark set. But these versions lacked precision, so that the meaningful parallels could be found only among long lists of those that were not meaningful. The Version 3 search described here adds a second stage scoring system that sorts the found parallels by a formula accounting for word frequency and phrase density. Testing against a benchmark set of intertexts in Latin epic poetry shows that the scoring system overall succeeds in ranking parallels of greater significance more highly, allowing site users to find meaningful parallels more quickly. Users can also choose to adjust both recall and precision by focusing only on results above given score levels. As a theoretical matter, these tests establish that lemma identity, word frequency, and phrase density are important constituents of what make a phrase parallel a meaningful intertext.
      pubtype: Academic Journal
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      src: R
    language: English
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