Stylometric Analysis in the Task of Searching for Borrowings of Texts in the Tatar Language
https://doi.org/10.26907/1562-5419-2025-28-5-1267-1278
Abstract
This article discusses the use of stylometric analysis in searching for borrowings of text in the Tatar language. Relevant tools have been developed, utilizing machine learn-ing algorithms, including clustering (k-means method), classification (random forest method, support vector machine method, naive Bayes classifier), and a hybrid approach (FastText model + logistic regression). Special attention is paid to the adaptation of lin-guistic metrics for the Tatar language.
About the Authors
Izida Zufarovna Khayaleeva
Kazan (Volga region) Federal University
Russian Federation
Russian Federation
Mikhail Mikhailovich Abramskiy
Kazan (Volga region) Federal University
Russian Federation
Russian Federation
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Review
For citations:
Khayaleeva I.Z., Abramskiy M.M. Stylometric Analysis in the Task of Searching for Borrowings of Texts in the Tatar Language. Russian Digital Libraries Journal. 2025;28(5):1267-1278. (In Russ.) https://doi.org/10.26907/1562-5419-2025-28-5-1267-1278
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