KFU. Card publication. Using Text Vectorization to Analyze Students' Answers Formulated in Different Languages

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

USING TEXT VECTORIZATION TO ANALYZE STUDENTS' ANSWERS FORMULATED IN DIFFERENT LANGUAGES

Form of presentation

Articles in international journals and collections

Year of publication

2024

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Authors, employees of KFU

Minnegalieva Chulpan Bakievna, author

Bibliographic description in the original language

Minnegalieva C., Using Text Vectorization to Analyze Students' Answers Formulated in Different Languages//Proceedings - 4th International Conference on Technological Advancements in Computational Sciences, ICTACS 2024. - 2024. - Vol., Is.. - P.1262-1266.

Keywords

Language model, BERT, Automated short answer grading, Vector representation of the document, Cosine similarity

The name of the journal

Proceedings - 4th International Conference on Technological Advancements in Computational Sciences, ICTACS 2024

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85218213360&doi=10.1109%2fICTACS62700.2024.10841100&partnerID=40&md5=d7d6a3bc5914a5f040a4e375b272c22f

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=310546&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Minnegalieva Chulpan Bakievna	ru_RU
dc.date.accessioned	2024-01-01T00:00:00Z	ru_RU
dc.date.available	2024-01-01T00:00:00Z	ru_RU
dc.date.issued	2024	ru_RU
dc.identifier.citation	Minnegalieva C., Using Text Vectorization to Analyze Students' Answers Formulated in Different Languages//Proceedings - 4th International Conference on Technological Advancements in Computational Sciences, ICTACS 2024. - 2024. - Vol., Is.. - P.1262-1266.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=310546&p_lang=2	ru_RU
dc.description.abstract	Proceedings - 4th International Conference on Technological Advancements in Computational Sciences, ICTACS 2024	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Language model	ru_RU
dc.subject	BERT	ru_RU
dc.subject	Automated short answer grading	ru_RU
dc.subject	Vector representation of the document	ru_RU
dc.subject	Cosine similarity	ru_RU
dc.title	Using Text Vectorization to Analyze Students' Answers Formulated in Different Languages	ru_RU
dc.type	Articles in international journals and collections	ru_RU