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Mining Feature-Opinion from Reviews Based on Dependency Parsing

机译:基于依赖分析的评论挖掘特征意见

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摘要

The manual reading of all the product reviews to find a satisfying item is not only labor-intensive, but also tedious for the consumers. In this paper, we propose a feature-opinion mining approach to automatically summarize the reviews, which is based on dependency parsing. Specifically, in our approach we first utilize a regression model to generate sentiment word, including phrase and its sentiment weight, and then we extract the feature based on the dependency relationship between feature word and sentiment word, finally we assign a score to the feature according to the dependency relationship. The experimental results demonstrate that our approach can effectively mine the feature-opinion from reviews.
机译:手动阅读所有产品评论以找到满意的商品不仅劳动强度大,而且对于消费者而言也是乏味的。在本文中,我们提出了一种基于特征分析的特征意见挖掘方法来自动汇总评论。具体来说,在我们的方法中,我们首先利用回归模型来生成情感词,包括短语及其情感权重,然后根据特征词与情感词之间的依存关系提取特征,最后根据到依赖关系。实验结果表明,我们的方法可以有效地从评论中挖掘特征观点。

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  • 作者单位

    State Key Laboratory of Novel Software Technology Nanjing University, Nanjing, Jiangsu 210023, P. R. China;

    State Key Laboratory of Novel Software Technology Nanjing University, Nanjing, Jiangsu 210023, P. R. China;

    State Key Laboratory of Novel Software Technology Nanjing University, Nanjing, Jiangsu 210023, P. R. China;

    State Key Laboratory of Novel Software Technology Nanjing University, Nanjing, Jiangsu 210023, P. R. China;

    School of Economics, Nanjing University Nanjing, Jiangsu 210023, P. R. China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    E-commerce; opinion analysis; dependency parsing;

    机译:电子商务;意见分析;依赖解析;

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