Benchmarking Multilabel Topic Classification in the Kyrgyz Language
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AZTNZLRBF" target="_blank" >RIV/00216208:11320/25:ZTNZLRBF - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189534275&doi=10.1007%2f978-3-031-54534-4_2&partnerID=40&md5=6cdf90a491807386e10b466d8ff58f40" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189534275&doi=10.1007%2f978-3-031-54534-4_2&partnerID=40&md5=6cdf90a491807386e10b466d8ff58f40</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-54534-4_2" target="_blank" >10.1007/978-3-031-54534-4_2</a>
Alternative languages
Result language
angličtina
Original language name
Benchmarking Multilabel Topic Classification in the Kyrgyz Language
Original language description
Kyrgyz is a very underrepresented language in terms of modern natural language processing resources. In this work, we present a new public benchmark for topic classification in Kyrgyz, introducing a dataset based on collected and annotated data from the news site 24.KG and presenting several baseline models for news classification in the multilabel setting. We train and evaluate both classical statistical and neural models, reporting the scores, discussing the results, and proposing directions for future work. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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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
Lect. Notes Comput. Sci.
ISBN
978-303154533-7
ISSN
0302-9743
e-ISSN
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Number of pages
15
Pages from-to
21-35
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
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Event location
Jerevan
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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