Machine Learning in Terminology Extraction from Czech and English Texts

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F21%3A10436228" target="_blank" >RIV/00216208:11210/21:10436228 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=vQFuByhTjv" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=vQFuByhTjv</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/lf-2021-0014" target="_blank" >10.2478/lf-2021-0014</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Machine Learning in Terminology Extraction from Czech and English Texts

Popis výsledku v původním jazyce

The method of automatic term recognition based on machine learning is focused primarily on the most important quantitative term attributes. It is able to successfully identify terms and non-terms (with success rate of more than 95%) and find characteristic features of a term as a terminological unit. The single-word term can be characterized as a word with a low frequency that occurs considerably more often in specialized texts than in non-academic texts, occurs in a small number of disciplines, its distribution in the corpus is uneven as is the distance between its two instances. The multi-word term is a collocation consisting of words with low frequency and contains at least one single-word term. The method is based on quantitative features and it makes it possible to utilize the algorithms in multiple disciplines as well as to create cross-lingual applications (verified on Czech and English).

Název v anglickém jazyce

Machine Learning in Terminology Extraction from Czech and English Texts

Popis výsledku anglicky

The method of automatic term recognition based on machine learning is focused primarily on the most important quantitative term attributes. It is able to successfully identify terms and non-terms (with success rate of more than 95%) and find characteristic features of a term as a terminological unit. The single-word term can be characterized as a word with a low frequency that occurs considerably more often in specialized texts than in non-academic texts, occurs in a small number of disciplines, its distribution in the corpus is uneven as is the distance between its two instances. The multi-word term is a collocation consisting of words with low frequency and contains at least one single-word term. The method is based on quantitative features and it makes it possible to utilize the algorithms in multiple disciplines as well as to create cross-lingual applications (verified on Czech and English).

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

60203 - Linguistics

Projekt

<a href="/cs/project/EF16_019%2F0000734" target="_blank" >EF16_019/0000734: Kreativita a adaptabilita jako předpoklad úspěchu Evropy v propojeném světě</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Linguistic Frontiers [online]

ISSN

2544-6339

e-ISSN

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Svazek periodika

4

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

23-30

Kód UT WoS článku

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EID výsledku v databázi Scopus

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