Abstract
Standardization and technical regulation involve the digitization of international and regional standards into "smart" standards, introducing new requirements for the presentation of complex industrial manuals. The introduction of artificial intelligence and machine learning into the process of standardization, improving process automation, data analysis will provide an opportunity to create innovative standards. Creation of machine-readable standards and their presentation in the form of a database will contribute to better interoperability between systems. The article demonstrates the method of ontological engineering for the automation of partial methodological examination of documents in accordance with the National Standardization Plan. As part of the experiment, an independent tool was developed, based on the extraction of qualitative data, using an uncontrolled automatic keyword extraction algorithm. The algorithm does not require the creation of a learning corpus, can be applied to any text and language, and does not have limitations on the amount of processed data. The algorithm provides adjustment of the parameters of the repetition of keywords, with the possibility of taking into account less important keywords. The work presents the following components: model classification standards, essence extraction module, categorization, thesaurus formation, monitoring and analysis. Calculations were carried out using formalization, determination of the target function, establishment of similarity measures, and description of document features. The work presents the theoretical aspect of application, design and description of the functional system.