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New Technology of Library and Information Service  2011, Vol. 27 Issue (10): 54-62    DOI: 10.11925/infotech.1003-3513.2011.10.10
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A Method and Its Application of Text Semantic Orientation
Xu Xin1, Yu Fei1, Zhang Li2
1. Department of Informatics, East China Normal University, Shanghai 200241, China;
2. Department of Computer Science and Technology, Nanjing University, Nanjing 210093, China
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Abstract  This paper firstly introduces the model and technology of text classification, especially analyzes and compares two methods of text semantic orientation based on both statistical and semantic analysis. Then it proposes pattern matching based on the extraction and text classification algorithm, and evaluate this algorithm. Finally, the authors describe the technical implementation and fields application of text semantic orientation.
Key wordsText semantic orientation      Sentiment classification      Semantic orientation      Network information     
Received: 18 August 2011      Published: 03 December 2011
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G353

 

Cite this article:

Xu Xin, Yu Fei, Zhang Li. A Method and Its Application of Text Semantic Orientation. New Technology of Library and Information Service, 2011, 27(10): 54-62.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2011.10.10     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2011/V27/I10/54

[1] Pang B,Lee L,Vaithyanathan S. Thumbs Up? Sentiment Classification Using Machine Learning Techniques . In:Proceedings of Conference on Empirical Methods in Natural Language Proeessing.2002:79-86.

[2] Salvetti F, Lewis S,Reiehenbach C. Automatic Opinion Polarity Classification of Movie Reviews[J]. Colorado Research in Linguistics,2004,17(1):1-15.

[3] 刘康,赵军.基于层叠CRFs模型的句子褒贬度分析研究[J]. 中文信息学报, 2008,22(l):123-128.

[4] 邹嘉彦.评述新闻报道或文章色彩——正负两极性自动分类的研究 .见: 自然语言理解与大规模内容计算——全国第八届计算语言学联合学术会议 .北京:清华大学出版社,2005:21-23.

[5] 时达明,林鸿飞.基于内容相关度和情感分析的Blogger声誉度研究 . 见: 第三届全国信息检索与内容安全学术会议 ,苏州.2007:656-662.

[6] 信息检索专业委员会评测专栏 . .http://www.ir-china.org.cn/coae2008.html.

[7] 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 . 见: 第五届全国信息检索学术会议论文集 ,上海.2009.

[8] Gamon M, Aue A, Corston-Oliver S, et al. Pulse: Mining Customer Opinions from Free Text . In:Proceedings of the 6th International Symposium on Intelligent Data Analysis.2005:121-132.

[9] Morinaga S, Yamanishi K, Tateishi K, et al. Mining Product Reputations on the Web . In:Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.2002:341-349.

[10] Tong R M. An Operational System for Detecting and Tracking Opinions in On-line Diseussion . In:Proceedings of Workshop Notes of the ACM SIGIR 2001Workshop on Operational Text Classification. 2001:1-6.

[11] Liu B, Hu M, Cheng J. Opinion Observer: Analyzing and Comparing Opinions on the Web . In:Proceedings of the 14th International Conference on World Wide Web.2005:342-351.

[12] 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 .见: 中国中文信息学会成立二十五周年学术年会 ,北京,中国.2006.

[13] Salton G, Wong A, Yang C S. A Vector Space Model for Automatic Indexing[J].Communications of the ACM,1975,18(5):613-620.

[14] Yang Y M, Pederson J O. A Comparative Study on Feature Selection in Text Categorization .In:Proceedings of the 14 International Conference on Machine learning.Bled: Morgan Kaufmann, 1997: 258-267.

[15] Sebastiani F. Machine Learning in Automated Text Categorization[J]. ACM Computing Surveys, 2002, 34(1):1-47.

[16] Paninski L.Estimation of Entropy and Mutual Information[J]. Neural Computation, 2003, 15(6):1191-1253.

[17] 高洁,吉根林.文本分类技术研究[J]. 计算机应用研究, 2004,21(7):28-30.

[18] 樊兴华,孙茂松. 一种高性能的两类中文文本分类方法[J]. 计算机学报, 2006,29(1):124-131.

[19] Van Campenhout J, Cover T. Maximum Entropy and Conditional Probability[J]. IEEE Transactions on Information Theory, 1981, 27(4):483-489.

[20] 李荣陆,王建会,陈晓云,等. 使用最大熵模型进行中文文本分类[J]. 计算机研究与发展, 2005,42(1):94-101.

[21] Osuna E, Freund R,Girosi F. An Improved Training Algorithm for Support Vector Machines . In:Proceedings of the 1997 IEEE Workshop on Neural Networks for Signal Processing.New York: IEEE Press, 1997:276-285.

[22] 都云琪,肖诗斌. 基于支持向量机的中文文本自动分类研究[J]. 计算机工程, 2002,28(11):137-138.

[23] General Inquirer . .http://www.wjh.harvard.edu/~inquirer/.

[24] 知网.http://www.keenage.com/.

[25] 张伟,刘缙,郭先珍.学生褒贬义词典[M].北京:中国大百科全书出版社,2004.

[26] 史继林,朱英贵.褒义词词典 [M]. 成都:四川辞书出版社, 2005.

[27] 杨玲,朱英贵.贬义词词典[M]. 成都:四川辞书出版社, 2005.

[28] 梅家驹, 竺一鸣,高蕴琦,等. 同义词词林[M]. 上海:上海辞书出版社,1983.

[29] 同义词词林扩展版 . .http://www.ir-lab.org/.

[30] 李荣陆.文本分类若干关键技术研究 .上海:复旦大学, 2005.

[31] 中文情感挖掘语料ChnSentiCorp . .http://www.searchforum.org.cn/tansongbo/corpus-senti.htm.

[32] 黄仲清. 互联网主题信息定向采集研究 . 上海:华东师范大学, 2010.

[33] ICTCLAS汉语分词系统.http://ictclas.org/.

[34] Hu N, Liu L, Zhang J.Analyst Forecast Revision and Market Sales Discovery of Online . In:Proceedings of the 40th Hawaii International Conference on System Sciences.2007.

[35] 当当图书畅销榜.http://bang.dangdang.com/book/bestSeller/.
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