ANALYSIS OF RESEARCH ON THESAURUS IN COMPUTATIONAL LINGUISTICS

Abstract

This article provides a comprehensive analysis of research on thesaurus development and application within the field of computational linguistics. Thesauri, as structured lexical-semantic resources, play a crucial role in natural language processing (NLP), information retrieval, and knowledge representation systems. The study examines the evolution of thesaurus-based approaches, including traditional lexicographic models and modern computational frameworks such as WordNet and ontology-based systems. Special attention is given to corpus-based methods, semantic similarity modeling, and automated thesaurus construction techniques, which have significantly improved the accuracy and scalability of linguistic databases. Recent studies highlight the importance of identifying inconsistencies in lexical relations and enhancing semantic networks through data- driven approaches. Furthermore, the article explores multilingual and domain- specific thesauri, emphasizing their relevance in modern AI-driven applications. The findings demonstrate that thesauri remain fundamental tools for organizing linguistic knowledge and facilitating intelligent text processing, while ongoing research continues to refine their structure, interoperability, and practical implementation in computational systems.