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 изданияхстатья

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 оригиналаанглийский
Страницы (с-по)120-126
Число страниц7
ЖурналAutomatic documentation and mathematical linguistics
Том51
Номер выпуска3
DOI
СостояниеОпубликовано - 1 июн 2017

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