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基于语境情感消岐的评论倾向性分析 被引量:6

Sentiment Analysis of Comments Based on Contextual Emotional Disambiguation
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摘要 研究评论倾向性分析中情感词的动态极性变化问题.用Apriori算法在语境基础上挖掘情感歧义词语搭配,构建出(情感对象,情感词,情感倾向性)三元组形式的情感歧义词搭配词典,利用条件随机场模型(CRFs)序列标注方法从评论文本中抽取出情感要素,在构建的情感歧义词搭配词典基础上对评论文本进行了细粒度情感倾向性分析.在手机和电脑两个领域的评论语料集上进行多组实验,与传统方法的对比实验表明了方法的可行性,较为明显地提高了情感倾向性分析的准确率. The problem of dynamic polarity change in sentiment analysis was studied.Apriori algorithm was used to expand the sentiment ambiguous words based on context, and constructed the sentiment ambiguous lexicon of triples (namely sentiment object, sentiment word, sentiment polarity).CRFs was used to extracted sentiment elements from comments.Finally, the completed fine-grained sentiment analysis based on the sentiment ambiguous lexicon was conducted.Multiple sets of experiments were performed on two domains of mobile phones and computers.Compared with the traditional method, the experimental results showed the feasibility of the proposed method and the improved accuracy of sentiment analysis.
出处 《郑州大学学报(理学版)》 CAS 北大核心 2017年第2期48-53,共6页 Journal of Zhengzhou University:Natural Science Edition
基金 国家自然科学基金项目(61373148) 山东省科技发展计划项目(2014GGX101004)
关键词 情感歧义词 语境 细粒度 情感要素 CRFs sentiment ambiguous words CRFs context fine-grained sentiment elements
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  • 1朱嫣岚,闵锦,周雅倩,黄萱菁,吴立德.基于HowNet的词汇语义倾向计算[J].中文信息学报,2006,20(1):14-20. 被引量:326
  • 2车万翔.面向依存文法分析的搭配抽取方法研究[C]..见:全国第六届计算语言学联合学术会议[C].,2001.102-107.
  • 3姚天昉,聂青阳,李建超,李林琳,陈柯,付宁.一个用于汉语汽车评论的意见挖掘系统[C]//中文信息处理前沿进展-中国中文信息学会二十五周年学术会议论文集.北京:清华大学出版社,2006:260-281.
  • 4李素建,刘群.汉语组块的定义和获取[C]//孙茂松,陈群秀.语言计算与基于内容的文本处理:全国计算语言学联合学术会议(SWCL2003)论文集.北京:清华大学出版社,2003:110-115.
  • 5Bolshakov IA,Gelbukh A.Heuristics-BasedReplenishment of Collocation Databases[J].E.M.Ranchhod and N.J.Mamede(Eds.),2002,2389:25-32.
  • 6Ding XW,Liu B,Yu PS.A Holistic Lexicon-BasedApproach To Opinion Mining[C] //Proceedings of TheConference on Web Search And Web Data Mining(WSDM).New York:ACM,2008:231-240.
  • 7Agrawal R,Imielinski T,Swami AN.-MiningAssociation Rules Between Sets of Items In Large DataBases[C] //Proceedings of The ACM SIGMOD IntlConference on Management of Data.Washington:1993:207-216.
  • 8Agrawal R,Srikant R.Fast Algorithms For MiningAssociation Rules[C] //The Proceedings of IntelConference on Very Large Data Bases.Santiago:1994:487-499.
  • 9Kim SM,Hovy E.Automatic Detection of OpinionBearing Words And Sentences[C] //The Proceedingsof IJCNLP-2005.JeJu Island:2005:61-66.
  • 10Zhao J,Liu K.Adding redundant features for crfs-based sentence sentiment classification[C] //TheProceedings of The 2008 Conference on EmpiricalMethods In Natural Language Processing.Honolulu:2008:117-126.

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