KFU. Card publication. Thesaurus-Based Methods for Assessment of Text Complexity in Russian

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

THESAURUS-BASED METHODS FOR ASSESSMENT OF TEXT COMPLEXITY IN RUSSIAN

Form of presentation

Articles in international journals and collections

Year of publication

2020

Язык

английский

Authors, employees of KFU

Ivanov Vladimir Vladimirovich, author

Solnyshkina Marina Ivanovna, author

Solovev Valeriy Dmitrievich, author

Bibliographic description in the original language

Solovyev V., Ivanov V., Solnyshkina M. (2020) Thesaurus-Based Methods for Assessment of Text Complexity in Russian. In: Martínez-Villaseñor L., Herrera-Alcántara O., Ponce H., Castro-Espinoza F.A. (eds) Advances in Computational Intelligence. MICAI 2020. Lecture Notes in Computer Science, vol 12469. Springer, Cham. https://doi.org/10.1007/978-3-030-60887-3_14

Annotation

The study explores the problem of assessing complexity of Russian educational texts. In this paper, we focus on measuring conceptual complexity which is rarely selected as a research question and propose to use a thesaurus (or a linguistic ontology) to this end. We also compiled an original corpus of school textbooks on Social Studies, History used in high school, and textbooks for elementary school specifically for this set of text complexity experiments. On the first stage of the research, RuThes-Lite thesaurus, a linguistic knowledge base with the total size of 100,000 concepts, was used to elicit concepts in the texts of schoolbooks and represent them as graphs. To the best of our knowledge, we a new method for text complexity assessment using RuThes-Lite graphs and identify graphs-based semantic characteristics of texts that impact complexity. The most significant findings of the research include identification of statistically significant correlations of the selected features, such as node degree, with complexity of educational texts.

Keywords

Text complexity, Thesaurus, Russian language

The name of the journal

Lecture Notes in Computer Science Proceedings, Springer. - LNCS 3777.

URL

https://link.springer.com/chapter/10.1007/978-3-030-60887-3_14

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

https://repository.kpfu.ru/eng/?p_id=239434&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Ivanov Vladimir Vladimirovich	ru_RU
dc.contributor.author	Solnyshkina Marina Ivanovna	ru_RU
dc.contributor.author	Solovev Valeriy Dmitrievich	ru_RU
dc.date.accessioned	2020-01-01T00:00:00Z	ru_RU
dc.date.available	2020-01-01T00:00:00Z	ru_RU
dc.date.issued	2020	ru_RU
dc.identifier.citation	Solovyev V., Ivanov V., Solnyshkina M. (2020) Thesaurus-Based Methods for Assessment of Text Complexity in Russian. In: Martínez-Villaseñor L., Herrera-Alcántara O., Ponce H., Castro-Espinoza F.A. (eds) Advances in Computational Intelligence. MICAI 2020. Lecture Notes in Computer Science, vol 12469. Springer, Cham. https://doi.org/10.1007/978-3-030-60887-3_14	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=239434&p_lang=2	ru_RU
dc.description.abstract	Lecture Notes in Computer Science Proceedings, Springer. - LNCS 3777.	ru_RU
dc.description.abstract	The study explores the problem of assessing complexity of Russian educational texts. In this paper, we focus on measuring conceptual complexity which is rarely selected as a research question and propose to use a thesaurus (or a linguistic ontology) to this end. We also compiled an original corpus of school textbooks on Social Studies, History used in high school, and textbooks for elementary school specifically for this set of text complexity experiments. On the first stage of the research, RuThes-Lite thesaurus, a linguistic knowledge base with the total size of 100,000 concepts, was used to elicit concepts in the texts of schoolbooks and represent them as graphs. To the best of our knowledge, we a new method for text complexity assessment using RuThes-Lite graphs and identify graphs-based semantic characteristics of texts that impact complexity. The most significant findings of the research include identification of statistically significant correlations of the selected features, such as node degree, with complexity of educational texts.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Text complexity	ru_RU
dc.subject	Thesaurus	ru_RU
dc.subject	Russian language	ru_RU
dc.title	Thesaurus-Based Methods for Assessment of Text Complexity in Russian	ru_RU
dc.type	Articles in international journals and collections	ru_RU