Chinese Text Classification Based on Ant Colony Optimization

被引：0
|
作者：
Luo Xin [1 ]
机构：
[1] S China Univ Technol, Coll Business Adm, Guangzhou 510641, Guangdong, Peoples R China
来源：
PROCEEDINGS OF THE 2015 4TH NATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER ENGINEERING ( NCEECE 2015) | 2016年 / 47卷
关键词：
Text processing; classification; Artificial intelligence; Ant colony optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
It's significance for us to study Chinese Text Classification, when we face so much dynamic information. The development of Text Classification has a close connection with Pattern Recognition. However, some peculiarity of Chinese Text Classification, such as it has many classes, much noise, and excessive samples, make Pattern Recognition difficult to classify texts. Recently, Artificial Intelligence provides a new intellectualized method to Text Classification. This paper tentatively leads Ant Colony Optimization, a ripe algorithm of Swarm Intelligence, into Text Classification. We construct a Text ACO-Miner Classification Model based on Ant Colony Optimization, and test it. The result shows the model can accurately be used to classify Chinese texts.
引用
收藏
页码：37 / 41
页数：5
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