计算机科学 ›› 2012, Vol. 39 ›› Issue (6): 159-162.

• 数据库与数据挖掘 • 上一篇    下一篇

评价主题挖掘及其倾向性识别

李芳,何婷婷,宋乐   

  1. (华中师范大学国家数字化学习工程技术研究中心 武汉 430079)(华中师范大学计算机科学系 武汉 430079) (国家语言资源监测与研究中心网络媒体分中心 武汉 430079)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Opinion Topic Mining and Orientation Identification

  • Online:2018-11-16 Published:2018-11-16

摘要: 主要研究如何从在线评论文本中挖掘产品的评价主题,并对其倾向性进行分析。首先采用一种启发式规则和共现概率统计相结合的方法识别文本集合中的名词性短语,再运用LDA模型挖掘潜在的评价主题。然后利用多特征融合的方法计算句子的倾向性,进而根据特征词群统计出各主题的倾向性结果。最后通过对网络汽车评论文本语料的实验证实了该方法的有效性。

关键词: LDA,评价主题,倾向性识别

Abstract: hhe paper mainly focused attention on how to mine opinion topic from online subjective text set,and identified the orientation of these opinion topics. It combined the heuristic rule and co-occurrence probability to identify area noun phrase, and adopted Latent Dirichlet Allocationn(LDA) to obtain local opinion topic. Then, it computed the sentence orientation with a method of multiple features fusion, and obtained the opinion topic orientation by adding up the number of each orientation of the sentences belonging to the specified topic. Experimental results show that the method can identify the topic and their orientation effectively.

Key words: LDA, Opinion topic, Orientation identification

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