Multi-Domain Sentiment Classification with Classifier Combination

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 自然语言处理

	Multi-Domain Sentiment Classification with Classifier Combination
	Li, Shou-Shan; Huang, Chu-Ren; Zong, Cheng-Qing
发表期刊	JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
	2011
卷号	26 期号:1;1 页码:25-33
文章类型	Article
摘要	State-of-the-arts studies on sentiment classification are typically domain-dependent and domain-restricted. In this paper, we aim to reduce domain dependency and improve overall performance simultaneously by proposing an efficient multi-domain sentiment classification algorithm. Our method employs the approach of multiple classifier combination. In this approach, we first train single domain classifiers separately with domain specific data, and then combine the classifiers for the final decision. Our experiments show that this approach performs much better than both single domain classification approach (using the training data individually) and mixed domain classification approach (simply combining all the training data). In particular, classifier combination with weighted sum rule obtains an average error reduction of 27.6% over single domain classification.
关键词	Sentiment Classification Multiple Classifier System Multi-domain Learning
WOS标题词	Science & Technology ; Technology
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS记录号	WOS:000286866900004
引用统计	被引频次：26[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/40936
专题	多模态人工智能系统全国重点实验室_自然语言处理
推荐引用方式 GB/T 7714	Li, Shou-Shan,Huang, Chu-Ren,Zong, Cheng-Qing. Multi-Domain Sentiment Classification with Classifier Combination[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2011,26(1;1):25-33.
APA	Li, Shou-Shan,Huang, Chu-Ren,&Zong, Cheng-Qing.(2011).Multi-Domain Sentiment Classification with Classifier Combination.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,26(1;1),25-33.
MLA	Li, Shou-Shan,et al."Multi-Domain Sentiment Classification with Classifier Combination".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 26.1;1(2011):25-33.