Comparative Research on Automatic Classification Algorithms Based on Chinese Medical Literature

DOI

10.2991/ncce-18.2018.33How to use a DOI?

Keywords

Chinese Medical Literature, Automatic Classification, SVM, BP Neural Network, Random Forest

Abstract

With the development of electronic periodicals, it is unavoidable that there are some classification management problems. But currently the classification management of papers basically majors in manual classification. Based on Chinese medical literature, this essay compares and analyzes these automatic classification algorithms: support vector machine (SVM), BP neural network, and random forest. It is found that SVM is more suitable for automatic classification of Chinese medical literature

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Kai An
AU  - Yunqiu Zhang
AU  - Xiaoyang Wang
AU  - Zhe Jiang
AU  - Chenglong Wang
AU  - Xiang Zhu
PY  - 2018/05
DA  - 2018/05
TI  - Comparative Research on Automatic Classification Algorithms Based on Chinese Medical Literature
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 198
EP  - 206
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.33
DO  - 10.2991/ncce-18.2018.33
ID  - An2018/05
ER  -