电邮这篇文章 Classification by compression: Application of information-theory methods for the identification of themes of scientific texts
- 作者: Selivanova I.V.1, Ryabko B.Y.2,3, Guskov A.E.2,3
-
隶属关系:
- The State Public Scientific Technological Library, Siberian Branch
- Novosibirsk State University
- Institute of Computational Technologies, Siberian Branch
- 期: 卷 51, 编号 3 (2017)
- 页面: 120-126
- 栏目: Information Analysis
- URL: https://journals.rcsi.science/0005-1055/article/view/150170
- DOI: https://doi.org/10.3103/S0005105517030116
- ID: 150170
如何引用文章
开放存取
##reader.subscriptionAccessGranted##
订阅存取
详细
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.
作者简介
I. Selivanova
The State Public Scientific Technological Library, Siberian Branch
编辑信件的主要联系方式.
Email: selivanova@ict.sbras.ru
俄罗斯联邦, Novosibirsk, 123298
B. Ryabko
Novosibirsk State University; Institute of Computational Technologies, Siberian Branch
Email: selivanova@ict.sbras.ru
俄罗斯联邦, Novosibirsk, 630090; Novosibirsk, 630090
A. Guskov
Novosibirsk State University; Institute of Computational Technologies, Siberian Branch
Email: selivanova@ict.sbras.ru
俄罗斯联邦, Novosibirsk, 630090; Novosibirsk, 630090
补充文件
