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现代图书情报技术  2012, Vol. Issue (10): 61-66    DOI: 10.11925/infotech.1003-3513.2012.10.10
  情报分析与研究 本期目录 | 过刊浏览 | 高级检索 |
商品在线评价的情感倾向性分析研究
张红斌1, 李广丽2
1. 华东交通大学软件学院 南昌 330013;
2. 华东交通大学信息工程学院 南昌 330013
Research on Sentiment Orientation Analysis of Product Online Reviews
Zhang Hongbin1, Li Guangli2
1. School of Software, East China Jiaotong University, Nanchang 330013, China;
2. School of Information Engineering, East China Jiaotong University, Nanchang 330013, China
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摘要 围绕商品在线评论的语义挖掘问题,采用情感倾向性分析技术对商品在线评论进行情感倾向性极性分析,在此基础上定量度量情感倾向性强度,以正确地表达商品在线评论信息的语义内涵。选择淘宝网小米手机和摩托罗拉ME525+手机的在线评论进行实验分析,结果表明本研究获取的情感倾向性自动评分的准确率达到80%以上,且绝大多数的商品属性指标均能保证正确的情感倾向性极性。因此,该研究成果对用户的网上购物具有一定的参考价值。
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张红斌
李广丽
关键词 情感倾向性分析商品在线评论Rost EAHeritrix正则表达式    
Abstract:This paper aims at resolving the semantic mining problem of product online reviews by using the technology of sentiment orientation analysis. The sentiment orientation polar is firstly analyzed and the intensity of sentiment orientation analysis is computed to correctly express the inner semantic of product online reviews. The reviews of Xiaomi mobile phone and Motorola ME525+ mobile phone on Taobao are chosen to do the experiments. The results show that the precision of each auto-scoring of sentiment orientation analysis can reach 80% and most attribute indicators of products can get correct sentiment orientation polar, Which can help Web users to make correct purchase decisions to some extent.
Key wordsSentiment orientation analysis    Product online reviews    Rost EA    Heritrix    Regular expression
收稿日期: 2012-07-11     
:  TP391  
基金资助:本文系教育部人文社会科学研究青年项目“基于多层语义推理的数字图书馆多媒体信息检索模型研究”(项目编号:12YJCZH274)、教育部人文社会科学研究青年项目“融合跨媒体检索的数字图书馆个性化信息推送服务研究”(项目编号:11YJC870012)和江西省科技支撑计划-社会发展项目“基于跨媒体检索的医学肿瘤图像病变语义诊断”(项目编号:20121BBG70050)的研究成果之一。
通讯作者: 张红斌     E-mail: zhbdog@tom.com
引用本文:   
张红斌, 李广丽. 商品在线评价的情感倾向性分析研究[J]. 现代图书情报技术, 2012, (10): 61-66.
Zhang Hongbin, Li Guangli. Research on Sentiment Orientation Analysis of Product Online Reviews. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2012.10.10.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2012.10.10
[1] Turney P D, Littman M L. Measuring Praise and Critism: Inference of Semantic Orientation From Association[J]. ACM Tanslations on Information Systems,2003,21(4):315-346.
[2] Zhang Z Q, Li Y J, Ye Q, et al. Sentiment Classification for Chinese Product Reviews Using an Unsupervised Internet-based Method[C]. In: Proceedings of 2008 International Conference on Management Science & Engineering(ICMSE 2008). 2008: 3-9.
[3] 朱嫣岚,闵锦,周雅倩,等. 基于HowNet的词汇语义倾向计算[J]. 中文信息学报,2006,20(1):14-20.(Zhu Yanlan, Min Jin, Zhou Yaqian, et al. Semantic Orientation Computing Based on HowNet[J]. Journal of Chinese Information Processing, 2006,20(1):14-20.)
[4] Hu M Q, Liu B.Mining Opinion Features in Customer Reviews[C].In: Proceedings of the 19th National Conference on Artificial Intelligence. AAAI Press, 2004: 755-760.
[5] Wiebe J, Rfloff E. Creating Subjective and Objective Sentence Classifiers from Unannotated Texts[C]. In: Proceeding of the 6th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2005). Berlin,Heidelberg: Springer-Verlag, 2005: 486-497.
[6] 王根,赵军.基于多重冗余标记 CRF 的句子情感分析研究[C].见: 内容计算的研究与应用前沿——第九届全国计算语言学学术会议论文集,2007.(Wang Gen, Zhao Jun. Sentence Sentiment Analysis Based on Multi-redundant-labeled CRF[C]. In: Proceedings of the 9th National Language Academic Conference,2007.)
[7] Pang B, Lee L, Vaithyanathan S. Thumbs up? Sentiment Classification Using Machine Learning Techniques[C]. In: Proceeding of the ACL-02 Conference on Empirical Methods in Natural Language Processing (EMNLP’02). Stroudsburg: Association for Computational Linguistics, 2002: 79-86.
[8] 左维松, 昝红英, 张坤丽, 等. 规则和统计相结合的情感分析研究[C]. 见: 第五届信息检索学术会议论文集,2009.(Zuo Weisong, Zhan Hongying, Zhang Kunli, et al. Sentiment Analysis Based on Rule and Statistics[C]. In: Proceedings of CCIR,2009.)
[9] 赵丽芳. 基于最大熵方法的评论信息抽取研究[D]. 上海:上海交通大学,2009.(Zhao Lifang. Research of Opinion Information Extraction Based on Maximum Entropy Model[D]. Shanghai: Shanghai Jiaotong University, 2009.)
[10] Liu B, Hu M Q, Cheng J S. Opinion Observer: Analyzing and Comparing Opinions on the Web[C].In: Proceeding of the 14th International Conference on World Wide Web (WWW’05). New York: ACM, 2005:342-351.
[11] 姚天昉, 聂青阳, 李建超, 等. 一个用于汉语汽车评论的意见挖掘系统[C]. 见: 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,2006. (Yao Tianfang, Nie Qingyang, Li Jianchao, et al. An Opinion Mining System for Chinese Automobile Reviews[C].In: Proceedings of the 25th Annual Academic Conference of Chinese Information, 2006.)
[12] Java正则表达式实例教程[EB/OL].[2012-08-31]. http://wenku.baidu.com/view/fcdf770bf78a6529647d5321.html. (Case Course of Java Regular Expression[EB/OL].[2012-08-31]. http://wenku.baidu.com/view/fcdf770bf78a6529647d5321.html.)
[13] Rost虚拟学习团队. Rost情感分析工具[EB/OL].[2012-08-31].http://www.fanpq.com/soft/uploadsoft/ROSTEA.rar.(Rost Virtual Learning Team. Rost Sentiment Analysis Tool[EB/OL].[2012-08-31]. http://www.fanpq.com/soft/uploadsoft/ROSTEA.rar.)
[14] 陈伟.无比强大的网络爬虫Heritrix[EB/OL].[2012-01-16]. http://wenku.baidu.com/view/46a9336a561252d380eb6e44.html. (Chen Wei. Incomparable Powerful Webcrawler Heritrix[EB/OL].[2012-01-16]. http://wenku.baidu.com/view/46a9336a561252d380eb6e44.html.)
[15] SourceForge. JFreeChart[EB/OL]. [2012-08-31]. http://sourceforge.net/projects/jfreechart/files/.
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