Approach to extracting text classification decision rules based on incomplete information systems

被引：0
|
作者：
Wang, Haiyong [1 ]
Yuyu, Meng [1 ]
Liying, Zheng [1 ]
机构：
[1] Lanzhou Jiaotong Univ, Sch Elect & Informat Engn, Lanzhou 730070, Peoples R China
来源：
2007 International Symposium on Computer Science & Technology, Proceedings | 2007年
关键词：
rough set; incomplete information system; text classification; rule reduction;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The extraction and optimization of a Text classification rules is the main indicator to evaluate the ability to adapt and classify of a Text classification system. Based on rough sets and fuzzy clustering theory of text classification system, along with the theory of incomplete information system, the paper presents the method to extract and optimize a classification rule. After experimenting and analysis, it raises satisfaction reduction rules to users, and makes users so quickly to classification the new text, it does enhance the ability to adapt and classify of the system.
引用
收藏
页码：263 / 265
页数：3
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