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基于CRFs的评价对象抽取特征研究 被引量:38

Feature Engineering for CRFs Based Opinion Target Extraction
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摘要 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。 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.
出处 《中文信息学报》 CSCD 北大核心 2012年第2期56-61,共6页 Journal of Chinese Information Processing
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
关键词 情感分析 评价对象抽取 特征组合 语义角色标注 sentiment analysis opinion target extraction the combination of features semantic role labeling
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参考文献12

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