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Erschienen in: Scientific and Technical Information Processing 6/2022

01.12.2022

Ontology Application in Automating Regulatory Profile Forming for Software Certification

verfasst von: Iu. I. Butenko

Erschienen in: Scientific and Technical Information Processing | Ausgabe 6/2022

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Abstract

The paper describes the methodology for the automation of regulatory profiles forming software certification. It has been noted that currently, the practical evaluation for software certification at the stage of regulatory profile formation is largely a manual analysis of large volumes of normative and project documentation submitted by texts in natural language that leads to a certain subjectivity of expert assessments and reduces their completeness and reliability. The degree of automation of the procedure for the formation of a regulatory profile is analyzed. The structure of the regulatory profile, the types of regulatory profiles, as well as options for its formation are given. The typical errors that can occur when automating the procedure of regulatory profiles formation are discussed. It is substantiated that it is advisable to use the ontological environment to automate the procedure for forming a regulatory profile. A model of the compositional structure of a standard text is presented. The use of a semantic integrity kernel for the user request reflecting the relationship between subject and predicate lexical units is proposed. The results of this study can be used in the development of an intelligent decision-making dialogue system for an auditor of the certification center to improve the efficiency of the auditor’s work by automating the routine process, as well as reducing the risk of making the wrong decision due to insufficient qualification of the person making the decision.

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Metadaten
Titel
Ontology Application in Automating Regulatory Profile Forming for Software Certification
verfasst von
Iu. I. Butenko
Publikationsdatum
01.12.2022
Verlag
Pleiades Publishing
Erschienen in
Scientific and Technical Information Processing / Ausgabe 6/2022
Print ISSN: 0147-6882
Elektronische ISSN: 1934-8118
DOI
https://doi.org/10.3103/S0147688222060028

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