MODELING BLOG USER FOR CHINESE MICRO-BLOG SENTIMENT CLASSIFICATION WITH FUZZY SVM

被引:0
|
作者
Sun, Xiao [1 ]
Li, Chengcheng [1 ]
Ren, Fuji [1 ,2 ]
机构
[1] Hefei Univ Technol, Sch Comp & Informat, Anhui Prov Key Lab Affect Comp & Adv Intelligent, Hefei 230009, Peoples R China
[2] Univ Tokushima, Fac Engn, Tokushima 7708506, Japan
基金
国家杰出青年科学基金;
关键词
sentiment classification; multidimensional; fuzzy SVM;
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
Micro-blog IS easily posted and communicated because of its short text length. Meanwhile, its brevity limits the feature expression. This paper presents a blogger modeling method for Chinese micro-blog sentiment classification. The paper would adopt a multidimensional strategy to accomplish the feature extraction task. Compared with traditional feature extraction methods and combined with the interactive property of blog, the blog comment will be considered as the performance characteristic of micro-blog emotion expression. It comes to comments content and the relationship between commentators and micro-bloggers while it extracts the micro blogging text feature. At last, the paper adopts fuzzy SVM model to reduce the sensation of noise points and outliers on classification problem. The results demonstrate the effectiveness of the multidimensional feature extraction method on sentiment classification and the classify effect of fuzzy SVM is better than SVM.
引用
收藏
页码:130 / 134
页数:5
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