Мақаланы E-mail арқылы жіберу Classification by compression: Application of information-theory methods for the identification of themes of scientific texts
- Авторлар: Selivanova I.V.1, Ryabko B.Y.2,3, Guskov A.E.2,3
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Мекемелер:
- The State Public Scientific Technological Library, Siberian Branch
- Novosibirsk State University
- Institute of Computational Technologies, Siberian Branch
- Шығарылым: Том 51, № 3 (2017)
- Беттер: 120-126
- Бөлім: Information Analysis
- URL: https://journals.rcsi.science/0005-1055/article/view/150170
- DOI: https://doi.org/10.3103/S0005105517030116
- ID: 150170
Дәйексөз келтіру
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Рұқсат берілді
Тек жазылушылар үшін
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.
Авторлар туралы
I. Selivanova
The State Public Scientific Technological Library, Siberian Branch
Хат алмасуға жауапты Автор.
Email: selivanova@ict.sbras.ru
Ресей, Novosibirsk, 123298
B. Ryabko
Novosibirsk State University; Institute of Computational Technologies, Siberian Branch
Email: selivanova@ict.sbras.ru
Ресей, Novosibirsk, 630090; Novosibirsk, 630090
A. Guskov
Novosibirsk State University; Institute of Computational Technologies, Siberian Branch
Email: selivanova@ict.sbras.ru
Ресей, Novosibirsk, 630090; Novosibirsk, 630090
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