Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/59511
Type of publication: Straipsnis konferencijos medžiagoje Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or Scopus DB conference proceedings (P1a)
Field of Science: Filologija / Philology (H004)
Author(s): Grigonytė, Gintarė;Kovalevskaitė, Jolanta;Rimkutė, Erika
Title: Linguistically-motivated automatic classification of Lithuanian texts for didactic purposes
Is part of: Human language technologies - the Baltic perspective: proceedings of the 8th international conference Baltic HLT, Tartu, Estonia, 27-29 September 2018 / editors K. Muischnek and K. Müürisep. Amsterdam : IOS Press, 2018
Extent: p. 38-46
Date: 2018
Series/Report no.: (Frontiers in artificial intelligence and applications, Vol. 307 0922-6389)
Note: Knygos ISBN 978-1-61499-912-6 (online)
Keywords: Lithuanian language;Linguistically-motivated automatic classification;Levelled study corpus
ISBN: 9781614999119
Abstract: This paper presents an effort to provide a level-appropriate study corpus for Lithuanian language learners. The collected corpus includes levelled texts from study books and unlevelled texts from other sources. The main goal is to assign the level-appropriate labels (A1, A2, B1, B2) to texts from other sources. For automatic classification we use preselected surface features, based on text readability research, and shallow linguistic features. First, we train the model with levelled texts from study books; second, we apply the learned model to classifying other texts. The best classification results are achieved with Logistic Regression method
Internet: https://hdl.handle.net/20.500.12259/59511
https://hdl.handle.net/20.500.12259/59511
http://ebooks.iospress.nl/volumearticle/50302
Affiliation(s): Humanitarinių mokslų fakultetas
Lituanistikos katedra
Užsienio kalbų, lit. ir vert. s. katedra
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

Files in This Item:
marc.xml8.02 kBXMLView/Open

MARC21 XML metadata

Show full item record

Page view(s)

298
checked on Nov 2, 2019

Download(s)

32
checked on Nov 2, 2019

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.