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Leveraging Part-of-Speech Tagging for Enhanced Stylometry of Latin Literature

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3APIVB2Q86" target="_blank" >RIV/00216208:11320/25:PIVB2Q86 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204761991&partnerID=40&md5=eec752a11f0ab7da8956eb75d64f827a" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204761991&partnerID=40&md5=eec752a11f0ab7da8956eb75d64f827a</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Leveraging Part-of-Speech Tagging for Enhanced Stylometry of Latin Literature

  • Original language description

    In literary critical applications, stylometry can benefit from hand-curated feature sets capturing various syntactic and rhetorical functions. For premodern languages, calculation of such features is hampered by a lack of computational resources for accurate part-of-speech tagging and semantic disambiguation. This paper reports an evaluation of POS taggers for Latin and their use in augmenting a hand-curated stylometric feature set. Our analyses show that POS-augmented features not only provide more accurate counts but also perform well on tasks such as genre classification. In the course of this work, we introduce POS n-grams as a feature for Latin stylometry. © 2024 Association for Computational Linguistics.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    ML4AL - Workshop Mach. Learn. Anc. Lang., Proc. Workshop

  • ISBN

    979-889176144-5

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    251-259

  • Publisher name

    Association for Computational Linguistics (ACL)

  • Place of publication

  • Event location

    Hybrid, Bangkok

  • Event date

    Jan 1, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article