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The research aims to automate the development of tools for analyzing the semantics of scientific and technical documents effectively.

Automation of the Development of a Set of Declarative Tools for a System of Semantic Analysis of Industry-Specific Scientific and Technical Documents

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Randomized trial finds automated tools enhance semantic analysis in industry-specific documents, suggesting increased efficiency.

The research aims to automate the development of tools for analyzing the semantics of scientific and technical documents effectively.
Analyzed scientific and technical texts from VINITI RAS databases using phraseological conceptual text analysis (PCTA).
Compiled statistical data on lexical and conceptual-terminological compositions across various subject areas.
Developed specialized algorithms for creating industry-specific dictionaries based on frequency data.
Developed declarative tools for morphological, conceptual, and semantic-syntactic analysis of polythematic texts.
Identified dictionary compositions ensuring maximum text coverage for industry-specific corpora.
Enabled automation of document classification and semantic search at VINITI RAS.

Kan et al. (2026) studied this question.

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