CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
Sentiment Classification of Chinese Contrast Sentences
Li, Junjie1; Zhou, Yu1; Liu, Chunyang2; Pang, Lin2
2014-12
Conference NameThe 3rd CCF Conference on Natural Language Processing & Chinese Computing
Conference Date2014-12
Conference PlaceShenzhen, China
Abstract

We present the study of sentiment classification of Chinese contrast
sentences in this paper, which are one of the commonly used language constructs in text. In a typical review, there are at least around 6% of such sentences. Due to the complex contrast phenomenon, it is hard to use the traditional bag-of-words to model such sentences. In this paper, we propose a Two-Layer Logistic Regression (TLLR) model to leverage such relationship in sentiment classification. According to different connectives, our model can treat different clauses differently in sentiment classification. Experimental results show that TLLR model can effectively improve the performance of sentiment classification of Chinese contrast sentences.
 

Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23104
Collection模式识别国家重点实验室_自然语言处理
Corresponding AuthorZhou, Yu
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
2.National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing, 100029
Recommended Citation
GB/T 7714
Li, Junjie,Zhou, Yu,Liu, Chunyang,et al. Sentiment Classification of Chinese Contrast Sentences[C],2014.
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