北京大学学报(自然科学版)

面向微博短文本的细粒度情感特征抽取方法

贺飞艳1,何炎祥1,刘楠1,2,刘健博1,彭敏1   

  1. 1. 武汉大学计算机学院, 武汉 430072; 2. 军事经济学院军需系, 武汉 430035;
  • 收稿日期:2012-05-20 出版日期:2014-01-20 发布日期:2014-01-20

A Microblog Short Text Oriented Multi-class Feature Extraction Method of Fine-Grained Sentiment Analysis

HE Feiyan1, HE Yanxiang1, LIU Nan1,2, LIU Jianbo1, PENG Min1   

  1. 1. School of Computer,Wuhan University, Wuhan 430072; 2. Department of Quartermaster, Military Economic Academy, Wuhan 430035;
  • Received:2012-05-20 Online:2014-01-20 Published:2014-01-20

摘要: 结合TF-IDF方法与方差统计方法, 提出一种实现多分类特征抽取的计算方法。采用先极性判断, 后细粒度情感判断的处理方法, 构建细粒度情感分析与判断流程, 并将其应用于微博短文本的细粒度情感判断。通过NLP&CC2013评测所提供的训练语料对该方法有效性进行验证, 结果表明该方法具有较好的抽取效果。

关键词: 自然语言处理, 文本情感分析, 细粒度情感, 多分类特征抽取

Abstract: Combined with TF-IDF method and variance statistical forumla, a new method for the extraction of multi-class feature is presented. This microblog short text oriented extraction method is used to determine the fine-grained sentiment type. Then the processes of fine-grained sentiment analysis is bulit. This method is used to praticipate the NLP&CC2013 evaluation, and the effectiveness of this method is proved by the good ranking of the subimitted data.

Key words: natural language processing, text sentiment analysis, fine-grained sentiment analysis, multi-class feature extraction

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