Optimization of Feature-Opinion Pairs in Chinese Customer Reviews

被引：0
|
作者：
Huang, Yongwen [1 ]
He, Zhongshi [1 ]
Wang, Haiyan [2 ]
机构：
[1] Chongqing Univ, Coll Comp Sci, Chongqing 400044, Peoples R China
[2] Sichuan Fine Arts Inst, Art Hist Dept, Chongqing 400044, Peoples R China
来源：
NEXT-GENERATION APPLIED INTELLIGENCE, PROCEEDINGS | 2009年 / 5579卷
关键词：
Customer reviews; Reviews mining; Bootstrapping; Harmonic-mean;
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：
Customer reviews mining can urge manufacturers to improve product quality and guide people a rational consumption. The commonly used mining methods are not satisfactory in precision of the features and opinions extracting. In this paper, we extracted the product features and opinion words in a unified process with semi-supervised learning algorithm, and made an adjustment of the threshold value of confidence to obtain a better mining performance, then adjusted the features sequence with big standard deviation, and maximized the harmonic-mean to raise the precision while ensured the recall. The experiment results show that our techniques are very effective.
引用
收藏
页码：747 / +
页数：2
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