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J4  2011, Vol. 45 Issue (7): 1167-1174    DOI: 10.3785/j.issn.1008-973X.2011.07.005
计算机科学技术     
文本倾向性分析综述
厉小军1,戴霖1,施寒潇1,黄琦2
1.浙江工商大学 计算机与信息工程学院,浙江 杭州 310018;
2.浙江大学 计算机科学与技术学院,浙江 杭州 310027
Survey on sentiment orientation analysis of texts
LI Xiao-jun1, DAI Lin1, SHI Han-xiao1, HUANG Qi2
1.School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China;
2. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
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摘要:

介绍文本倾向性分析的基本流程,从主观性文本识别、文本倾向性分析方法、现有系统及评测方法、语料库建设4个方面对现有文本倾向性分析技术进行介绍和概括.综述了文本倾向性分析的3类研究方法:简单统计方法、机器学习方法和细粒度情感相关性分析方法,分析这3类研究方法的特点,从算法复杂性、效率和适用范围等方面比较各自的优缺点.概括现有研究的成就和不足,从基础性问题、具体应用的实现方法2个方面提出研究的前景.

Abstract:

The basic flow of sentiment orientation analysis of texts was introduced, and the primary four aspects of current interesting researches were presented: subjectivity text recognition, sentiment orientation analysis method of texts, existing systems and evaluation methods, construction of corpus. Then three methods and their characteristics were summarized, i.e. simple statistics, machine learning and fine-grained sentiment relative analysis method. Merits and demerits of methods were analyzed from complexity, efficiency and applicable scope. Finally, the current achievements and shortages were summarized, and forecasted research perspectives were proposed including basic problem and implementation method of specific application.

出版日期: 2011-07-01
:  TP 18  
基金资助:

浙江省重大科技专项资助项目(2008C13082);浙江省自然科学基金资助项目(Y1090688);中央高校基本科研业务费专项资金资助项目(2009QNA5025).

通讯作者: 黄琦,男,副教授.     E-mail: kylehq@163.com
作者简介: 厉小军(1974-),男,教授,从事企业信息管理、自然语言处理研究. E-mail: lixj@zjgsu.edu.cn
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引用本文:

厉小军,戴霖,施寒潇,黄琦. 文本倾向性分析综述[J]. J4, 2011, 45(7): 1167-1174.

LI Xiao-jun, DAI Lin, SHI Han-xiao, HUANG Qi. Survey on sentiment orientation analysis of texts. J4, 2011, 45(7): 1167-1174.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2011.07.005        https://www.zjujournals.com/eng/CN/Y2011/V45/I7/1167

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