Predicting the presence of inline citations in academic text using binary classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61384399%3A31140%2F23%3A00059964" target="_blank" >RIV/61384399:31140/23:00059964 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2023.nodalida-1.72.pdf" target="_blank" >https://aclanthology.org/2023.nodalida-1.72.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Predicting the presence of inline citations in academic text using binary classification
Original language description
Main topics of the document: language model; SciBERT; citation prediction
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
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
ISBN
978-99-1621-999-7
ISSN
1736-8197
e-ISSN
1736-6305
Number of pages
6
Pages from-to
717-722
Publisher name
University of Tartu Library
Place of publication
Estonsko
Event location
Tórshavn
Event date
May 22, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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