(untitled) (INTERNATIONAL CONFERENCE ON MODERN DEVELOPMENT OF PEDAGOGY AND LINGUISTICS, 2025)
This thesis explores the integration of electronic thesauri with search systems to improve information retrieval and natural language processing (NLP). Electronic thesauri enhance semantic analysis by identifying synonymy, antonymy, hypernymy, and hyponymy, enabling search engines to understand query intent more accurately. They expand search scope, improve ranking, and facilitate machine translation and AI-driven text analysis. The study highlights key methodologies in thesaurus construction, including linguistic resource integration and expert validation. By bridging computational linguistics and AI, electronic thesauri contribute to advanced text processing applications, knowledge graph development, and intelligent search functionalities.