DocumentCode :
3097045
Title :
Feature-level sentiment analysis for Chinese product reviews
Author :
Zhang, Haiping ; Yu, Zhengang ; Xu, Ming ; Shi, Yueling
Author_Institution :
Dept. of Comput. Sci., Hangzhou Dianzi Univ., Hangzhou, China
Volume :
2
fYear :
2011
fDate :
11-13 March 2011
Firstpage :
135
Lastpage :
140
Abstract :
The sentiment analysis for English product reviews has been widely researched in recent years, followed with many important achievements. Due to the special language traits of Chinese, the study on Chinese product reviews is much more difficult than the former. In this work, we focus on the finer-grained sentiment analysis for Chinese product reviews, that is feature-level based sentiment analysis. We propose a hybrid method which combines association rules and point-wise mutual information to extract the product features, and then take advantage of the sentiment dictionary - HowNet to analyze the opinion orientation expressed on the product features. The experiment result obtained shows the effectiveness and efficiency of our approach.
Keywords :
data mining; feature extraction; natural languages; retail data processing; Chinese product review; English product review; HowNet; association rules; feature level sentiment analysis; finer grained sentiment analysis; pointwise mutual information; product feature extraction; sentiment dictionary; Dictionaries; Digital cameras; Feature extraction; Filtering; Mobile handsets; Portable computers; Semantics; Chinese product reviews; feature extracting; feature-level sentiment analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Research and Development (ICCRD), 2011 3rd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-839-6
Type :
conf
DOI :
10.1109/ICCRD.2011.5764099
Filename :
5764099
Link To Document :
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