An approach to natural text classification using different types of classification features

Samara University Repository

Welcome to the Samara University repository!

This is an open electronic archive created to preserve and disseminate the scientific results of our university. The works of researchers, faculty members, and students are available to everyone for academic and research purposes.

The repository contains dissertations, research articles, educational and methodological materials, monographs, and regulatory documents. The collections cover a wide range of fields: from aerospace technologies, engine engineering, and computer science to history, linguistics, mathematics, and ecology. The archive brings together the scientific heritage of the university, including materials prepared during the period of Samara State Aerospace University and Samara State University.

Looking for publications by author, title, date, or subject? Full-text search will provide relevant results. Want to explore the academic life more closely? Browse materials by the universityâs organizational units.

Descriptions of all publications and articles available in the repository can be found in the libraryâs electronic catalog. Staff and students can log in via the menu "Login -> My Resource Archive" using their personal account credentials (SSAU_id).

Use the archive for study, research, and professional development!

Full metadata record

DC Field	Value	Language
dc.date	2017
dc.date.accessioned	2025-08-22T12:17:54Z	-
dc.date.available	2025-08-22T12:17:54Z	-
dc.date.issued	2017
dc.identifier.identifier	Dspace\SGAU\20170523\64158
dc.identifier.citation	Glazkova A.V. An approach to natural text classification using different types of classification features // Сборник трудов III международной конференции и молодежной школы «Информационные технологии и нанотехнологии» (ИТНТ-2017) - Самара: Новая техника, 2017. - С. 1824-1827.
dc.identifier.uri	http://repo.ssau.ru/jspui/handle/123456789/13595	-
dc.description.abstract	The article describes our approach to the task of text addressee detection. We consider four different types of classification features and suggest a step-by-step approach to text classification. In conclusion, the paper presents the results of the experiment that have been performed to check the classification accuracy using the proposed approach.
dc.language	en
dc.publisher	Новая техника
dc.title	An approach to natural text classification using different types of classification features
dc.type	Article
local.identifier.olduri	http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/An-approach-to-natural-text-classification-using-different-types-of-classification-features-64158
local.identifier.olduri	http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/An-approach-to-natural-text-classification-using-different-types-of-classification-features-64158
Appears in Collections:	Информационные технологии и нанотехнологии

Files in This Item:

File	Description	Size	Format
paper 328_1824-1827.pdf	Основная статья	579.94 kB	Adobe PDF	View/Open

Show simple item record