Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Corpus-Based Terms Extraction in Linguistics Domain for Indonesian Language

Bibliographic Data

ID22161368
AuthorsWahyu Maulana (Universitas Sumatera Utara), Eddy Setia (0000-0003-1247-5209, Universitas Sumatera Utara)
Year2022
Volume6
Issue2
Pages257-270
Publication date2022-10-30
Open AccessYes
TypeARTICLE
VenueJurnal KATA (JOURNAL)
Journal identifiersISSN: 2502-0706 • E-ISSN: 2502-0706
PublisherLembaga Layanan Pendidikan Tinggi - LLDIKTI - Wilayah X (PUBLISHER)
DOI10.22216/kata.v6i2.908
OpenAlexW4363610078
LanguageEN

This research aims to extract the mono-lexical and poly-lexical terms from linguistics domain in Indonesian language. As the terminology and lexicology concept is somehow blurry, this research applies CTT by Cabré to do the terms extraction procedure. The corpus-based terminology method is applied in this research to get the best mono-lexical and poly-lexical terms possible. To compile the general and the specialized corpus in this research, AntConc is applied as an instrument. Even though the result is noisy, further analysis about the term limitation manually makes this research semi-automatic. The result shows that the limitation in language and words structure helps this research to delimit the mono-lexical terms extracted in this research. Furthermore, the mono-lexical terms extracted act as the starting point for poly-lexical terms

Applied linguistics · Computational linguistics · Corpus linguistics · Indonesian · Lexical analysis · Lexical item · Lexicology · Linguistics · Natural language processing · Terminology · Computer Science · Lexicography and Language Studies · linguistics and terminology studies · Mathematics · Natural Language Processing Techniques · Philosophy · Artificial Intelligence

Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae