N. G. Petrenko

AI
5papers
26citations
Novelty20%
AI Score15

5 Papers

SEMar 24, 2018
Development of formal models, algorithms, procedures, engineering and functioning of the software system "Instrumental complex for ontological engineering purpose"

A. V. Palagin, N. G. Petrenko, V. Yu. Velychko et al.

The given paper considered a generalized model representation of the software system "Instrumental complex for ontological engineering purpose". Represented complete software system development process. Developed relevant formal models of the software system "Instrumental complex for ontological engineering purpose", represented as mathematical expressions, UML diagrams, and also described the three-tier architecture of the software system "Instrumental complex for ontological engineering purpose" in a client-server environment.

AIFeb 17, 2018
Technique for designing a domain ontology

A. V. Palagin, N. G. Petrenko, K. S. Malakhov

The article describes the technique for designing a domain ontology, shows the flowchart of algorithm design and example of constructing a fragment of the ontology of the subject area of Computer Science is considered.

AIFeb 13, 2018
Principles of design and software development models of ontological-driven computer systems

A. V. Palagin, N. G. Petrenko, V. Yu. Velychko et al.

This paper describes the design principles of methodology of knowledge-oriented information systems based on ontological approach. Such systems implement technology subject-oriented extraction of knowledge from the set of natural language texts and their formal and logical presentation and application processing

AIFeb 10, 2018
To the problem of "The Instrumental complex for ontological engineering purpose" software system design

A. V. Palagin, N. G. Petrenko, V. Yu. Velychko et al.

The given work describes methodological principles of design instrumental complex of ontological purpose. Instrumental complex intends for the implementation of the integrated information technologies automated build of domain ontologies. Results focus on enhancing the effectiveness of the automatic analysis and understanding of natural-language texts, building of knowledge description of subject areas (primarily in the area of science and technology) and for interdisciplinary research in conjunction with the solution of complex problems.