Using Semantic Correlation of HowNet for Short Text Classification

被引：2
|
作者：
Ning, Yahui [1 ]
Zhang, Li [1 ]
Ju, Yarong [1 ]
Wang, Weijia [1 ]
Li, Shunqin [1 ]
机构：
[1] Logist Engn Univ, Dept Logist Informat, Chongqing, Peoples R China
来源：
APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY | 2014年 / 513-517卷
关键词：
short-text; ontology; HowNet; text-classification; semantic;
D O I：
10.4028/www.scientific.net/AMM.513-517.1931
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
A method using the HowNet ontologies for short texts classification was proposed. First, the domain high frequency words were got as the feature words. Then the feature words were extended to concept by HowNet, which extended the feature from semantic and amends the feature scarcity. Last, the word semantic correlation values were got by calculating the distance between different concepts in node tree. Experimental results prove that the classification efficiency and precision are both improved.
引用
收藏
页码：1931 / 1934
页数：4
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