опрацювання природної мови

Due to the simplification of the processes of creating and distributing news via the Internet, as well as due to the physical impossibility of checking large volumes of information circulating in the network, the volume of disinformation and fake news distribution has increased significantly. A decision support system for identifying disinformation, fakes and propaganda based on machine learning has been built. The method of news text analysis for identifying fakes and predicting the detection of disinformation in news texts has been studied.

The article describes a study of identification of fake news based on natural language processing, big data analysis and deep learning technology. The developed system automatically checks the news for signs of fake news, such as the use of manipulative language, unverified sources and unreliable information. Data visualization is implemented on the basis of a friendly user interface that displays the results of news analysis in a convenient and understandable format.

 The article describes the results of research into the processes of complex analysis of military information based on machine learning and natural language processing to help commanders of tactical units. The system should allow users to have the following capabilities: combining the dictionary and information material, adding terms and abbreviations to the dictionary, classifying objects for radio technical intelligence, visualizing aerial objects, classifying aerial objects, using information materials, organizing information materials.

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.