Machine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century

We consider in this work linguostatistical methods that were used for attribution (establishing authorship) of publicistic articles of the XIX century. At that time, F. M. Dostoevsky edited and headed three journals: ""Time"", ""Epoch"" and ""Citizen...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Aleksandr Rogov, Nikolai Moskin, Kirill Kulakov, Roman Abramov
Formato:	article
Lenguaje:	EN
Publicado:	FRUCT 2021
Materias:	text attribution f. m. dostoevsky machine learning decision tree recurrent network transformer model smalt information system Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/df087c5bfdd8451da9e6aa5851c9594a
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:df087c5bfdd8451da9e6aa5851c9594a
record_format	dspace
spelling	oai:doaj.org-article:df087c5bfdd8451da9e6aa5851c9594a2021-11-20T15:59:33ZMachine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century2305-72542343-073710.23919/FRUCT53335.2021.9599961https://doaj.org/article/df087c5bfdd8451da9e6aa5851c9594a2021-10-01T00:00:00Zhttps://www.fruct.org/publications/fruct30/files/Rog.pdfhttps://doaj.org/toc/2305-7254https://doaj.org/toc/2343-0737We consider in this work linguostatistical methods that were used for attribution (establishing authorship) of publicistic articles of the XIX century. At that time, F. M. Dostoevsky edited and headed three journals: ""Time"", ""Epoch"" and ""Citizen"", where there are about 500 unattributed texts. Samples from texts were compiled, their characteristics were studied, and a comparative analysis of the classification results based on various machine learning methods (decision trees, recurrent networks, parallel recurrent networks, transformer model) was carried out. The input of texts, their processing and the calculation of linguostatistical parameters were carried out using an updated version of the SMALT information system.Aleksandr RogovNikolai MoskinKirill KulakovRoman AbramovFRUCTarticletext attributionf. m. dostoevskymachine learningdecision treerecurrent networktransformer modelsmalt information systemTelecommunicationTK5101-6720ENProceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 30, Iss 1, Pp 223-229 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	text attribution f. m. dostoevsky machine learning decision tree recurrent network transformer model smalt information system Telecommunication TK5101-6720
spellingShingle	text attribution f. m. dostoevsky machine learning decision tree recurrent network transformer model smalt information system Telecommunication TK5101-6720 Aleksandr Rogov Nikolai Moskin Kirill Kulakov Roman Abramov Machine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century
description	We consider in this work linguostatistical methods that were used for attribution (establishing authorship) of publicistic articles of the XIX century. At that time, F. M. Dostoevsky edited and headed three journals: ""Time"", ""Epoch"" and ""Citizen"", where there are about 500 unattributed texts. Samples from texts were compiled, their characteristics were studied, and a comparative analysis of the classification results based on various machine learning methods (decision trees, recurrent networks, parallel recurrent networks, transformer model) was carried out. The input of texts, their processing and the calculation of linguostatistical parameters were carried out using an updated version of the SMALT information system.
format	article
author	Aleksandr Rogov Nikolai Moskin Kirill Kulakov Roman Abramov
author_facet	Aleksandr Rogov Nikolai Moskin Kirill Kulakov Roman Abramov
author_sort	Aleksandr Rogov
title	Machine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century
title_short	Machine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century
title_full	Machine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century
title_fullStr	Machine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century
title_full_unstemmed	Machine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century
title_sort	machine learning methods in the problem of attribution of publicistic texts of the xix century
publisher	FRUCT
publishDate	2021
url	https://doaj.org/article/df087c5bfdd8451da9e6aa5851c9594a
work_keys_str_mv	AT aleksandrrogov machinelearningmethodsintheproblemofattributionofpublicistictextsofthexixcentury AT nikolaimoskin machinelearningmethodsintheproblemofattributionofpublicistictextsofthexixcentury AT kirillkulakov machinelearningmethodsintheproblemofattributionofpublicistictextsofthexixcentury AT romanabramov machinelearningmethodsintheproblemofattributionofpublicistictextsofthexixcentury
_version_	1718419455189450752

Machine Learning Methods in the Problem of Attribution of Publicistic Texts of the XIX Century

Ejemplares similares