An Algorithm for Title Classification on Scientific News
Authors
Wujie Shao, Hongjian Zhu, YunYang Yan, Quanyin Zhu
Corresponding Author
Wujie Shao
Available Online May 2016.
- DOI
- 10.2991/wartia-16.2016.373How to use a DOI?
- Keywords
- Text Categorization, Scientific News, Term Frequency, Machine Learning, Weighted Eigenvalue
- Abstract
Nowadays, with the rapid development of Internet, news is growing explosively. In order to improve the practical value of scientific news, an algorithm of text categorization which is used to classify scientific news is designed. The number of scientific news is 16034, which is gotten from web pages. During the experiment, scientific news of life, medical scientific news, scientific news of earth, mathematical and physical scientific news, chemical scientific news and informational scientific news respectively achieved 72.04%, 64.05%, 71.59%, 67.88%, 66.84% and 61.35% accuracy rate. This algorithm gets good effect and improves the value of the scientific news collected from Web and the accuracy of scientific news detailed classification.
- Copyright
- © 2016, 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/).
Cite this article
TY - CONF AU - Wujie Shao AU - Hongjian Zhu AU - YunYang Yan AU - Quanyin Zhu PY - 2016/05 DA - 2016/05 TI - An Algorithm for Title Classification on Scientific News BT - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications PB - Atlantis Press SP - 1881 EP - 1885 SN - 2352-5401 UR - https://doi.org/10.2991/wartia-16.2016.373 DO - 10.2991/wartia-16.2016.373 ID - Shao2016/05 ER -