MATHEMATICAL MODELING OF THE LEXICAL-SEMANTIC FIELD OF ANDREY SHEPTYTSKYI'S PASTORAL LETTERS USING MACHINE LEARNING ALGORITHMS

Yurii Hulyk

doi:10.23856/6204

Yurii Hulyk https://orcid.org/0009-0000-8030-1409

Keywords: pastoral letters, lexical and semantic field, machine learning, Word2Vec, text processing, NLP, TF-IDF, CBOW, Bag-of-Words, Skip-Gram

Abstract

This article explores the lexical and semantic field of Andrey Sheptytsky's pastoral letters using machine learning algorithms. To study the lexical and semantic field, such algorithms as Word2Vec, TF-IDF, CBOW, Bag-of-Words and Skip-Gram are used. The texts of this prominent figure are studied through the prism of modern methods of natural language processing, which allows for a more detailed identification of the peculiarities of their vocabulary and semantics. The article discusses the process of creating computer models for text analysis, as well as the use of machine learning algorithms for automatic processing and classification of lexical items in pastoral letters. The results obtained allow us to better understand the specifics of the author's language and mentality, as well as to identify patterns in the use of relevant words and expressions in his work. This work opens up new possibilities for the study of pastoral texts and deepening our understanding of their semantic properties.

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