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. |
| Keywords: | linguistics computational linguistics topic modeling large language models dentistry scientometric analysis bibliometric methods artificial intelligence |
| Issue Date: | 2025 |
| Citation: | Litvinova, T.A. From STM to GPT: a comparative study of topic modeling methods for AI in dentistry / T.A. Litvinova, Y.A. Ippolitov, P.V. Seredin // Научный результат. Сер. Вопросы теоретической и прикладной лингвистики. - 2025. - Т.11, №3.-С. 85-121. - Doi: 10.18413/2313-8912-2025-11-3-0-5. - Библиогр.: с. 116-120. |
| 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 |
| URI: | http://dspace.bsuedu.ru/handle/123456789/65961 |
| Appears in Collections: | Т. 11, № 3 |
| File | Description | Size | Format | |
|---|---|---|---|---|
| Litvinova_From_STM_25.pdf | 2.26 MB | Adobe PDF | View/Open |
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