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New Technology of Library and Information Service  2011, Vol. 27 Issue (7/8): 97-103    DOI: 10.11925/infotech.1003-3513.2011.07-08.16
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Design and Implementation of Semantic-based Sentiment Mining System
Li Gang, Wang Zhongyi
School of Information Management, Wuhan University, Wuhan 430072, China
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Abstract  Due to the complexity of natural language, there are still some problems existing in sentiment mining such as: domain dependence of sentiment words, implicit features recognition, synonym recognition, the calculation of the features' sentiment strengths and so on. To solve these problems, this paper proposes a sentiment mining method based on topic map. This method, which makes full use of the semantic relationships between feature words and sentiment words, can improve the accuracy of the sentiment mining to certain extent.
Key wordsSentiment mining      Topic map      Structure of features     
Received: 26 May 2011      Published: 09 October 2011



Cite this article:

Li Gang, Wang Zhongyi. Design and Implementation of Semantic-based Sentiment Mining System. New Technology of Library and Information Service, 2011, 27(7/8): 97-103.

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[1] Dave K, Lawrence S,Pennock D M. Mining the Peanut Gallery: Opinion Extraction and Semantic Classification of Product Reviews . In:Proceedings of the 12th International Conference on World Wide Web.2003:519-528.

[2] Pang B, Lee L. Opinion Mining and Sentiment Analysis[J]. Foundations and Trends in Information Retrieval, 2008, 2(1-2):1-135.

[3] Whitelaw C,Garg N, Argamon S. Using Appraisal Groups for Sentiment Analysis . In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, Bremen, DE.2005: 625-631.

[4] Gamon M, Aue A, Corstor-Oliver S, et al. Pulse: Mining Customer Opinions from Free Text . In: Proceedings of IDA-05, the 6th International Symposium on Intelligent Data Analysis, Madrid, Spain. Lecture Notes in Computer Science, Springer-Verlag,2005:121-132.

[5] Yang H, Si L, Callan J. Knowledge Transfer and Opinion Detection in the TREC 2006 Blog 36 Track . In: Proceedings of TREC.2006.

[6] 徐琳宏,林鸿飞,杨志豪. 基于语义理解的文本倾向性识别机制[J]. 中文信息学报, 2007,21(1):96-100.

[7] 张强,李乃和.网络口碑研究现状及未来发展初探[J]. 江西农业学报, 2008,20(4):147-149.

[8] Dey L, Haque S K M. Opinion Mining from Noisy Text Data[J]. International Journal on Document Analysis and Recognition, 2009, 12(3): 205-226.

[9] 李娟,张全,贾宁,等. 基于模板的中文人物评论意见挖掘[J]. 计算机应用研究, 2010,27(3):833-836.

[10] Gamon M, Aue A. Automatic Identification of Sentiment Vocabulary Exploiting Low Association with Known Sentiment Terms . In: Proceedings of the ACL-05 Workshop on Feature Engineering for Machine Learning in Natural Language Processing, Ann Arbor,US.2005:57-64.

[11] Hu M, Liu B. Mining Opinion Features in Customer Reviews .In: Proceedings of the 19th National Conference on Artificial Intelligence.2004: 755-760.
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