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Modelling and Data Analysis
2020. Vol. 10, no. 3, 24–38
doi:10.17759/mda.2020100302
ISSN: 2219-3758 / 2311-9454 (online)

Automatic Clustering of Mass Media Documents Based on the Analysis of Their Semantic Content

103

A.V. Kan, Y.D. Kozlovskaya, N.A. Kadushkin, A.A. Khoroshilov

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Abstract

The article describes the solution to the problem of automatic clustering of media documents based on the analysis of their semantic analysis. The proposed solution is based on the methods of machine grammar, semantic-syntactic and conceptual analysis of texts, as well as methods for identifying the conceptual composition of a collection of documents and formalizing the semantic content of texts. The developed algorithm of the document clustering process provides for the possibility of its implementation in a fully automatic mode without prior machine learning.

General Information

Keywords: automatic clustering of documents, machine grammar, semantic-syntactic analysis of texts, conceptual analysis of texts, actual conceptual vocabulary

Journal rubric: Data Analysis

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2020100302

For citation: Kan A.V., Kozlovskaya Y.D., Kadushkin N.A., Khoroshilov A.A. Automatic Clustering of Mass Media Documents Based on the Analysis of Their Semantic Content. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2020. Vol. 10, no. 3, pp. 24–38. DOI: 10.17759/mda.2020100302. (In Russ., аbstr. in Engl.)

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Information About the Authors

Anna V. Kan, PhD in Engineering, Associate Professor, Institute of Moscow Aviation Institute (National Research University), Head of the Analytical Department, Federal State Budgetary Institution «National Research Center» Institute named after N.E. Zhukovsky, Moscow, Russia, ORCID: https://orcid.org/0000-0001-9410-406X, e-mail: kan_a@mail.ru

Yana D. Kozlovskaya, Student, Institute of Moscow Aviation Institute (National Research University), Moscow, Russia, ORCID: https://orcid.org/0000-0002-1780-5687, e-mail: yana_kozlovskaia@mail.ru

Nikolay A. Kadushkin, Student, Institute of Moscow Aviation Institute (National Research University), Moscow, Russia, ORCID: https://orcid.org/0000-0002-0327-909X, e-mail: bbamrin@gmail.com

Aleksander A. Khoroshilov, Doctor of Engineering, Senior programmer, AO ″NPK “VT i SS”″, Moscow, Russia, ORCID: https://orcid.org/0000-0003-4885-3232, e-mail: a.a.horoshilov@mail.ru

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