Software for Classification of Texts in Russian by Functional Styles Basing on Parts of Speech Combinations in Sentences

Student: Osipov Maksim

Supervisor: Liliya Leonidovna Volkova

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Information Science and Computation Technology (Bachelor)

Year of Graduation: 2018

The aim of this work is to create software for the classification of texts in Russian by functional styles, taking into account the combination of parts of speech in sentences. The review of the existing methods of text analysis in order to highlight its features for further classification, as well as machine learning methods. It is offered to allocate morphological signs from the text as characteristic parameters, and on frequencies of use of their combinations in the text to carry out classification with use of the mechanism of a neural network. The software implementing the proposed approach has been developed and tested. The paper discusses the results of experimental measurements of accuracy on the data of the corpus of texts of three functional styles of the Russian language.

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