DocumentCode
3071803
Title
Sentiment Classification for Movie Reviews in Chinese by Improved Semantic Oriented Approach
Author
Ye, Qiang ; Shi, Wen ; Li, YiJun
Author_Institution
Harbin Institute of Technology
Volume
3
fYear
2006
fDate
04-07 Jan. 2006
Abstract
Sentiment classification aims at mining reviews of customers for a certain product by automatic classifying the reviews into positive or negative opinions. With the fast developing of World Wide Web applications, sentiment classification would have huge opportunity to help people automatic analysis of customers’ opinions from the web information. Automatic opinion mining will benefit to both consumers and sellers. Up to now, it is still a complicated task with great challenge. There are mainly two types of approaches for sentiment classification, machine learning methods and semantic orientation methods. Though some pioneer researches explored the approaches for English movie review classification, few jobs have been done on sentiment classification for Chinese reviews. The improved semantic approach for sentiment classification on movie reviews written in Chinese was proposed in this paper. Data experiment shows the capability of this approach.
Keywords
Chinese; Semantic Oriented; Sentiment classification; movie reviews; Cameras; Computer science; Data mining; Learning systems; Machine learning algorithms; Motion pictures; Mutual information; Search engines; Statistics; Technology management; Chinese; Semantic Oriented; Sentiment classification; movie reviews;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences, 2006. HICSS '06. Proceedings of the 39th Annual Hawaii International Conference on
ISSN
1530-1605
Print_ISBN
0-7695-2507-5
Type
conf
DOI
10.1109/HICSS.2006.432
Filename
1579396
Link To Document