System of classification for personnel selection based upon Ukrainian language ana-lyze

O.P. Zhezherun, M.S. Ryepkin


The article describes a classification system with natural language processing. Many systems use neural networks, but it needs massive amounts of data for training, which is not always available. Authors propose to use ontologies in such systems. As example of such approach it is shown the classification system, which helps to form a list of the best candidates during the recruitment process. An overview of the methods for ontologies constructing and language analyzers appropriate for classification systems are presented. The system in the form of a knowledge base is constracted. Described system supports Ukrainian and English languages. The  possible ways of system expansion is regarded.

Problems in programming 2020; 4: 34-40


classification system; knowledge base; ontology; Protégé; natural language processing; Ukrainian language processing


Glybovets A., Glybovets M., Polyakov M. Intelligent networks. NaUKMA. Dnipropetrovsk. 2014. 462 p.

Zhezherun O., Repkin M. Classification system for personnel selection. Scientific Notes of NaUKMA. 2019. CrossRef

Shynkaruk V. Philosophical encyclopedic dictionary. Kyiv: Grigory Skovoroda Institute of Philosophy: Abris. 2002. 742 р.

Lapshin V. Ontologies in information systems. Modern approach. Moscow. 2009.

Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies [Електронний ресурс].

Lovins Julie Beth. Development of a Stemming Algorithm. Mechanical Translation and Computational Linguistics. 1968. Т. 11.

Manning Christopher D., Raghavan Prabhakar, Schütze Hinrich. Introduction to Information Retreival. Cambridge University Press.

DeRose Steven J. Grammatical category disambiguation by statistical optimization. Computational Linguistics, 1988.



  • There are currently no refbacks.