Samara University Repository
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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.
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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).
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| Title: | An approach to natural text classification using different types of classification features |
| Issue Date: | 2017 |
| Publisher: | Новая техника |
| 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. |
| 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. |
| URI: | http://repo.ssau.ru/jspui/handle/123456789/13595 |
| Appears in Collections: | Информационные технологии и нанотехнологии |
| File | Description | Size | Format | |
|---|---|---|---|---|
| paper 328_1824-1827.pdf | Основная статья | 579.94 kB | Adobe PDF | View/Open |
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