Models for analyzing the complexity of english words in the text on the scale from A1 to C2

Скорочена інформація про документ
dc.contributor.authorBielikov, M.
dc.contributor.authorLikhouzova, T.
dc.contributor.authorOliinyk, Y.
dc.date.accessioned2024-11-12T10:59:55Z
dc.date.available2024-11-12T10:59:55Z
dc.date.issued2024
dc.description.abstractAt the current stage of globalization, English plays a key role as the language of international communication. This leads to the fact that more and more people become its carriers at various levels. The work is devoted to the analysis of English words on the scale from A1 to C2, which corresponds to the lowest and highest levels of proficiency according to the CEFR standards. A model that predicts the difficulty of words in a text can be used to improve the educational process. For example, it is possible to find a list of likely unknown and difficult words for the end user in any text depending on his level of English language proficiency. This approach will facilitate the language learning process by providing a personalized list of words to focus on. Also, the model can be useful for analyzing the complexity of texts depending on the number of words of each level of complexity in them. This can help teachers prepare materials that match the level of knowledge of their students, as well as identify words that may be difficult for them to understand. An application in the Python programming language is proposed, which receives a sample of data from the created storage, displays them graphically, performs intellectual analysis, trains and compares models according to accuracy, precision, recall and f1-score metrics. For data analysis and prediction of the level of complexity of English words, the following models were used: PchipInterpolator, logarithmic model, Gradient Boosting, Random Forest and XGB.
dc.format.pagerangeС. 84-99
dc.identifier.citationBielikov, M. Models for analyzing the complexity of english words in the text on the scale from A1 to C2 / M. Bielikov, T. Likhouzova, Y. Oliinyk // Адаптивні системи автоматичного управління : міжвідомчий науково-технічний збірник. – 2024. – № 2 (45). – С. 84-99. – Бібліогр.: 13 назв.
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/70515
dc.language.isoen
dc.publisherКПІ ім. Ігоря Сікорського
dc.publisher.placeКиїв
dc.rights.urihttps://creativecommons.ru/licenses
dc.sourceАдаптивні системи автоматичного управління : міжвідомчий науково-технічний збірник, № 2 (45), 2024
dc.subjectintelligent data analysis
dc.subjecttext analysis
dc.subjectclassification problem
dc.subjectaccuracy metrics
dc.subject.udc004.94
dc.titleModels for analyzing the complexity of english words in the text on the scale from A1 to C2
dc.typeArticle

Файли

Контейнер файлів
Зараз показуємо 1 - 1 з 1
Ескіз
Назва:
84-99.pdf
Розмір:
1.46 MB
Формат:
Adobe Portable Document Format
Завантажити
Ліцензійна угода
Зараз показуємо 1 - 1 з 1
Ескіз недоступний
Назва:
license.txt
Розмір:
8.98 KB
Формат:
Item-specific license agreed upon to submission
Опис:
Завантажити

Зібрання

Адаптивні системи автоматичного управління : міжвідомчий науково-технічний збірник. – 2024. – № 2 (45)