评价对象抽取是情感分析任务中一个重要的子任务。该文使用基于条件随机场模型的监督学习方法实现英文的评价对象抽取。为了更好的捕捉评价对象和情感词之间的关系,引入句法分析用以加入丰富的句法特征提高评价对象抽取性能。实验中,我们在两个不同的数据集上考查了句法特征对评价对象抽取性能的影响,并做了详细的分析比较。实验结果表明,将句法特征应用在评价对象抽取任务中能够取得不错的效果,明显提高了评价对象的抽取召回率。
Abstract
Opinion target extraction is an important sub-task of the sentiment analysis. This paper employs a supervised model to extract English opinion target with Conditional Random Fileds (CRFs). To better capture the relationship between the opinion targets and opinion expression, we add the syntactic features extracted from the parsing trees. In the experiments, two different data sets are used to evaluate the proposed approach. The experimental results demonstrate that using syntactic features is effective and it could improve the recall of opinion target extraction significantly.
关键词
情感分析 /
评价对象 /
句法特征 /
条件随机场
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Key words
Sentiment analysis /
Opinion target /
syntactic features /
CRF
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参考文献
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脚注
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基金
国家自然科学基金(61003155),国家自然科学基金(60873150),模式识别国家重点实验室开发课题基金。
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