Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts

In this paper we propose the algorithm of automated definition of the genre type and semantic characteristics of poetic texts in Russian. We formulated the approaches to the construction of a joint (“two-dimensional”) classifier of genre types and stylistic colouring of poetic texts, based on the de...

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Main Authors: Barakhnin Vladimir, Kozhemyakina Olga, Pastushkov Ilya
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:ITM Web of Conferences
Online Access:https://doi.org/10.1051/itmconf/20171002001
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spelling doaj-3fac87def7324c288f85eda632bc9a0a2021-04-02T11:17:22ZengEDP SciencesITM Web of Conferences2271-20972017-01-01100200110.1051/itmconf/20171002001itmconf_sa2017_02001Automated Determination of the Type of Genre and Stylistic Coloring of Russian TextsBarakhnin VladimirKozhemyakina Olga0Pastushkov Ilya1Novosibirsk State UniversityInstitute of Computational Technologies of SB RASIn this paper we propose the algorithm of automated definition of the genre type and semantic characteristics of poetic texts in Russian. We formulated the approaches to the construction of a joint (“two-dimensional”) classifier of genre types and stylistic colouring of poetic texts, based on the definition of interdependence of the type of genre and stylistic colouring of the text. On the basis of these approaches the principles of formation of the training samples for the algorithms for the definition of styles and genre types were analyzed. The computational experiments with a corpus of texts of the Lyceum lyrics of A.S.Pushkin were implemented, which showed good results in determining the stylistic colouring of poetic texts and sufficient results in determining the genres. The proposed algorithms can be used for automation of the complex analysis of Russian poetic texts, significantly facilitating the work of the expert in determining their styles and genres by providing appropriate recommendations.https://doi.org/10.1051/itmconf/20171002001
collection DOAJ
language English
format Article
sources DOAJ
author Barakhnin Vladimir
Kozhemyakina Olga
Pastushkov Ilya
spellingShingle Barakhnin Vladimir
Kozhemyakina Olga
Pastushkov Ilya
Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts
ITM Web of Conferences
author_facet Barakhnin Vladimir
Kozhemyakina Olga
Pastushkov Ilya
author_sort Barakhnin Vladimir
title Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts
title_short Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts
title_full Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts
title_fullStr Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts
title_full_unstemmed Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts
title_sort automated determination of the type of genre and stylistic coloring of russian texts
publisher EDP Sciences
series ITM Web of Conferences
issn 2271-2097
publishDate 2017-01-01
description In this paper we propose the algorithm of automated definition of the genre type and semantic characteristics of poetic texts in Russian. We formulated the approaches to the construction of a joint (“two-dimensional”) classifier of genre types and stylistic colouring of poetic texts, based on the definition of interdependence of the type of genre and stylistic colouring of the text. On the basis of these approaches the principles of formation of the training samples for the algorithms for the definition of styles and genre types were analyzed. The computational experiments with a corpus of texts of the Lyceum lyrics of A.S.Pushkin were implemented, which showed good results in determining the stylistic colouring of poetic texts and sufficient results in determining the genres. The proposed algorithms can be used for automation of the complex analysis of Russian poetic texts, significantly facilitating the work of the expert in determining their styles and genres by providing appropriate recommendations.
url https://doi.org/10.1051/itmconf/20171002001
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