Feature Selection for Chinese Online Reviews Sentiment Classification

被引：0
|
作者：
Chen, Xian [1 ]
Ma, Jing [1 ]
Lu, Yueming [1 ]
机构：
[1] Minist Educ, Key Lab Trustworthy Distributed Comp & Serv BUPT, Beijing 100876, Peoples R China
来源：
2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PROBLEM-SOLVING (ICCP) | 2013年
关键词：
feature selection; sentiment classification; empirical analysis;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Considering that traditional feature selection methods (DF, MI and IG) usually lost useful information, we propose the Feature Selection for Chinese Online Reviews Sentiment Classification (FSCSC), FSCSC takes empirical analysis into account and focus on how to effectively select different types of features based on statistical approaches to improve sentiment classification performance. FSCSC was tested on a Chinese online reviews corpus with a size of 4000 documents. The experiment indicates that FSCSC can improve the classification effectiveness.
引用
收藏
页码：79 / 82
页数：4
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