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The article is devoted to the study of methods and means of determining objects of radio technical intelligence using machine learning technologies and an ontological approach. A naіve Bayesian classifier was used to identify objects of radio technical intelligence. The Naive Bayes classifier is a machine learning algorithm used to classify objects based on probabilities. In this article, a naive Bayesian classifier is used to determine the classes to which objects of radio technical intelligence belong.

Since the first computer, researchers always try to simulate human behave.  For Chatbots, one of the first goals is to interact with the user like a human using Natural Language.  For Health chatbots, another goal is as much important: be able to provide the correct answer to the user request.  Over Years, many health chatbots have been developed for many fields such as cancer, diagnosis orientation, psychiatrics, etc.

The review and analysis of natural language processing methods (NLP) was carried out. Definitely a global criterion for evaluating the effectiveness NLP funds. Recommendations on the expediency of the use NLP funds are given

This paper surveys the problem of multiword expressions (MWE), which plays the important role in development of large-scale, linguistically sound natural language processing technology. Multiword expressions are expressions which are made up of at least 2 words and which can be syntactically and/or semantically idiosyncratic. This category includes such constructions as compound nouns, idioms and phrasal verbs.This paper deals with modern approaches to MWE stratification, extraction and identification.

A method for automatic correction of Ukrainian sentences is introduced. The method is based on dependency grammar and utilizes mutually exclusive hypothesis graph for word sense disambiguation. 37 % of ambiguous sentences which were correctly corrected as opposed to 14 % corrected by spell checker.