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Lyon, France
Aug. 22, 2011 to Aug. 27, 2011
ISBN: 978-0-7695-4513-4
pp: 249-252
ABSTRACT
Opinion mining became an active research topic in recent years due to its wide range of applications. A number of companies offer opinion mining services. One problem that has not been well studied so far is the representation model. In this paper, we propose a novel sentence level sentiment representation model. By taking the observation that lots of sentences which have complicated opinion relations can not be represented well by slots filling or feature-based model, the novel representation model sentiment graph is described in this paper. A supervised structural learning method is presented and used to construct sentiment graphs from sentences. Experimental results in a manually labeled corpus are given to show the effectiveness of the proposed approach.
INDEX TERMS
Opinion Mining, Sentiment Graph, Structural learning method
CITATION
Qi Zhang, Yuanbin Wu, Yan Wu, Xuanjing Huang, "Opinion Mining with Sentiment Graph", WI-IAT, 2011, Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on, Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on 2011, pp. 249-252, doi:10.1109/WI-IAT.2011.12
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