This paper examines formal methods for measuring semantic similarity in natural language processing. It discusses the concept of semantic similarity using mathematical and algorithmic models, such as vector-space, probabilistic, and graph-based approaches. Formal criteria for evaluating semantic similarity are proposed, and their links to generalization ability and computational features are scientifically supported. The findings offer a foundational framework for assessing and enhancing NLP algorithms.
| Mualliflar | Abdullayev, Elmurod Zaylobidinovich, Абдуллаев, Элмурод Зайлобидинович, Abdullayev, Elmurod Zaylobidinovich |
|---|---|
| Jurnal | Ilim ha’m ja’miyet |
| Nashr sanasi | 2026-05-16 |
| Son | 3-1 |
| Betlar | 7-10 |
| Til | uz_Latn |
tabiiy tilni qayta ishlash, semantik o‘xshashlik, formal model, vektor fazosi, algoritmik tahlil, обработка естественного языка, семантическое сходство, формальные методы, векторное представление, алгоритмический анализ, natural language processing, semantic similarity, formal methods, vector space model, algorithmic analysis
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