评价对象是情感分析中情感信息的一个重要组成部分。该文基于条件随机场模型,研究多种特征在评价对象抽取任务中的表现,并将特征归纳为词法、依存关系、相对位置、语义四大类别。其中,重点引入语义角色标注新特征。在实验中,我们在三个不同的数据集上考查了各个特征及其组合对系统性能的影响,作了详细地比较研究。另外,实验结果表明新提出的语义角色标注特征对评价对象抽取有很好地指示作用。
Abstract
Opinion target is an important component of sentiment information in sentiment analysis. This paper explores Conditional Random Fileds (CRFs) based opinion target extraction. After employing frequently used features in sentiment extraction, we summarize all the features into four categories, i.e. lexical, dependency, relative-position and semantic. More importantly, we propose using semantic role as a specific feature. Great efforts and detailed comparative studies have been made to evaluate the performance by exploring various features and their combination. Experimental results show that semantic role is a good indicator for opinion target.
Key wordssentiment analysis; opinion target extraction; the combination of features; semantic role labeling
关键词
情感分析 /
评价对象抽取 /
特征组合 /
语义角色标注
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Key words
sentiment analysis /
opinion target extraction /
the combination of features /
semantic role labeling
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参考文献
[1] Pang B., Lee L., Vaithyanathan S. Thumbs Up Sentiment Classification Using Machine Learning Techniques[C]//Proceedings of EMNLP-2002. 2002: 79-86.
[2] Li S., Huang C., Zong C. Multi-domain Sentiment Classification with Classifier Combination[J]. Journal of Computer Science and Technology (JCST), 2011, 26(1): 25-33 .
[3] Kim S., Hovy E. Extracting Opinions, Opinion Holders, and Topics Expressed in Online News Media Text[C]//Proceedings of the ACL Workshop on Sentiment and Subjectivity in Text. 2006: 1-8.
[4] Lafferty J., McCallum A., Pereira F. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data[C]//Proceedings of ICML-2001. 2001: 282-289.
[5] Jakob N., Gurevych I. Extracting Opinion Targets in a Single and Cross-Domain Setting with Conditional Random Fields[C]//Proceedings of EMNLP-2010. 2010: 1035-1045.
[6] Hu M, Liu B. Mining Opinion Features in Customer Reviews[C]//Proceedings of AAAI-2004. 2004: 755-760.
[7] 倪茂树,林鸿飞.基于关联规则和极性分析的商品评论挖掘[C]//第三届全国信息检索与内容安全学术会议.2007:628-634.
[8] Titov I., McDonald R. Modeling Online Reviews with Multi-grain Topic Models[C]//Proceedings of WWW-2008. 2008: 111-120.
[9] Lu Y., Zhai C., Sundaresan N. Rated aspect summarization of short comments[C]//Proceedings of WWW-2009. 2009: 131-140.
[10] Lu B. Identifying Opinion Holders and Targets with Dependency Parser in Chinese News Texts[C]//Proceedings of the NAACL HLT 2010 Student Research Workshop, Los Angeles, California. 2010: 46-51.
[11] Toprak C., Jakob N., Gurevych I. Sentence and Expression Level Annotation of Opinions in User-Generated Discourse[C]//Proceedings of ACL-2010. 2010: 575-584.
[12] Zhuang L., Jing F., Zhu X. Movie review mining and summarization[C]//Proceedings of CIKM-2006. 2006: 43-50.
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脚注
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基金
国家自然科学基金资助项目(61003155);国家自然科学基金资助项目(60873150);模式识别国家重点实验室开发课题基金资助项目
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