Application of neural network language models based on distributive semantics for ontological modeling of the domain

The article discusses the technology of automated formation of SKOS-ontologies for semantic modeling of the subject area, based on natural language texts analysis. The technology is based on neural network and distributive (vector) language models. A brief description of the content and formulation of the problem of extracting concepts and relations from natural language texts is given, the results of constructing a neural network classifier of SKOS relations using the Glove vector model, as well as an example of using the technology to construct a fragment of an applied SKOS ontology are given.