Classification by Compression: Application of Information-Theory Methods for the Identification of Themes of Scientific Texts

I. V. Selivanova; B. Y. A. Ryabko; A. E. Guskov

doi:10.3103/S0005105517030116

Classification by Compression: Application of Information-Theory Methods for the Identification of Themes of Scientific Texts

I. V. Selivanova, B. Y. A. Ryabko, A. E. Guskov

Результат исследования: Научные публикации в периодических изданиях › статья › рецензирование

Аннотация

A method for automatic classification of scientific texts based on data compression is proposed. The method is implemented and investigated based on the data from an archive of scientific texts (arXiv.org) and in the CyberLeninka scientific electronic library (CyberLeninka.ru). Experiments showed that the method correctly identified the themes of scientific texts with a probability of 75-95%; its accuracy depends on the quality of the original data.

Язык оригинала	английский
Страницы (с-по)	120-126
Число страниц	7
Журнал	Automatic documentation and mathematical linguistics
Том	51
Номер выпуска	3
DOI	https://doi.org/10.3103/S0005105517030116
Состояние	Опубликовано - 1 июн 2017

Предметные области OECD FOS+WOS

1.02 КОМПЬЮТЕРНЫЕ И ИНФОРМАЦИОННЫЕ НАУКИ

Доступ к документу

10.3103/S0005105517030116

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Classification by Compression : Application of Information-Theory Methods for the Identification of Themes of Scientific Texts. / Selivanova, I. V.; Ryabko, B. Y. A.; Guskov, A. E.

В: Automatic documentation and mathematical linguistics, Том 51, № 3, 01.06.2017, стр. 120-126.

Результат исследования: Научные публикации в периодических изданиях › статья › рецензирование

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AU - Ryabko, B. Y. A.

AU - Guskov, A. E.

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KW - thematic classification of texts

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KW - arXiv.org

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