http://dspace.bsuedu.ru/handle/123456789/65551 Sun, 05 Apr 2026 18:01:57 GMT 2026-04-05T18:01:57Z http://dspace.bsuedu.ru/handle/123456789/65964 Title: Культурный код в учебном дискурсе: корпусный и параметрический подходы Authors: Донцов, М. А.; Солнышкина, М. И.; Шелестова, О. В. Abstract: В работе осуществлен корпусный и параметрический анализ 785 наименований референтов культурного кода России в текстах учебников по русскому языку, литературе и истории для учащихся 5-9 классов РФ. В качестве источников наименований референтов использовались валидированные данные лингвистических, культурологических и социологических исследований Wed, 01 Jan 2025 00:00:00 GMT http://dspace.bsuedu.ru/handle/123456789/65964 2025-01-01T00:00:00Z http://dspace.bsuedu.ru/handle/123456789/65963 Title: Semantics in corpus linguistics: the basic colour term red in Modern Greek Authors: Serakioti, D. Abstract: This paper argues that electronic corpora provide a rich source of data and a useful tool for semantics. More specifically, collocations, semantic preference and semantic prosody of the basic colour term kókkinos ("red") in Modern Greek are examined, using text corpora, such as Greek electronic dictionaries, SEK (Corpus of Greek texts) and Educational Thesaurus of Greek Texts Wed, 01 Jan 2025 00:00:00 GMT http://dspace.bsuedu.ru/handle/123456789/65963 2025-01-01T00:00:00Z http://dspace.bsuedu.ru/handle/123456789/65962 Title: Sudden fiction through the lens of decoding stylistics Authors: Panasenko, N. Abstract: The main purpose of the research is primarily to consider different types of stylistics focusing on decoding stylistics and its basic features, such as coupling, convergence, semantic repetition, salient feature and text strong position together with defeated expectancy. The subsidiary goals are to examine sudden fiction as a very specific genre in the prism of decoding stylistics and to specify types of oregrounding typical of it Wed, 01 Jan 2025 00:00:00 GMT http://dspace.bsuedu.ru/handle/123456789/65962 2025-01-01T00:00:00Z http://dspace.bsuedu.ru/handle/123456789/65961 Title: From STM to GPT: a comparative study of topic modeling methods for AI in dentistry Authors: Litvinova, T. A.; Ippolitov, Y. A.; Seredin, P. V. Abstract: This study presents a comprehensive topic modeling analysis of scientific abstracts in the field of artificial intelligence (AI) applied to dentistry. Three complementary approaches were compared: Structural Topic Modeling (STM); embedding-based clustering using the Leiden algorithm on OpenAI text embeddings; and zero-shot GPT-based topic modeling Wed, 01 Jan 2025 00:00:00 GMT http://dspace.bsuedu.ru/handle/123456789/65961 2025-01-01T00:00:00Z