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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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GIVING FORMAL RELATIONS BETWEEN WORDS IN A PARALLEL CORPUS (EXAMPLE OF UZBEK-GERMAN LANGUAGES)

descriptionPublicationkeyboard_double_arrow_right Article 27 May 2024Publisher:Zenodo
Authors: Rakhimova Sh.S.;

doi: 10.5281/zenodo.11356499 , 10.5281/zenodo.11356500

GIVING FORMAL RELATIONS BETWEEN WORDS IN A PARALLEL CORPUS (EXAMPLE OF UZBEK-GERMAN LANGUAGES)

Abstract

This article is about the linguistic basis of giving the formal relations between words in the Uzbek-German parallel corpus, and it was found that linguistic corpora are widely used in explaining the practical use of the language and the specific features of the language. Also, in the article, the programs developed through computer technologies for corpus linguistics, their differences, and the opinion of a group of scientists on corpus linguistics are mentioned

Keywords

characteristics of corpus linguistics, parallel corpus, corpus linguistics models, intercultural communication, corpus linguistics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average