INTEGRATING MORPHOLOGICAL ANALYSIS INTO MACHINE LEARNING MODELS FOR LANGUAGE PROCESSING - Sultanbayeva Oltinoy Omonbay kizi (Ta’limda raqamli texnologiyalarni tadbiq etishning zamonaviy tendensiyalari va rivojlanish omillari, 2025)
Annotation: This thesis explores the integration of linguistic morphological analysis into machine learning models for natural language processing (NLP). It focuses on how the inclusion of explicit morphological features, such as roots, affixes, and grammatical tags, can improve tasks like lemmatization. The study targets morphologically rich languages and uses both theoretical frameworks and experimental evaluation to support the findings.