Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
References 1. Arjun Mukherjee, Bing Liu(2012) “Aspect Extraction through Semi-Supervised Modeling”, In support NSF (IIS-1111092), pp.1 -10. 2. B. Liu (2010), “Sentiment Analysis and Subjectivity”, Handbook of Natural Language Processing, Second Edition. 3. Bing Liu (2010), “Sentiment Analysis: A Multi-Faceted Problem”, IEEE Intelligent Systems, pp.1-5. 4. Bing Liu, Minqing Hu, Junsheng Cheng (2005), “Opinion Observer: Analyzing and Comparing Opinions on the Web”, International World Wide Web Conference Committee (IW3C2), ACM, pp.1-10. 5. B. Pang and L. Lee (2008), “Opinion Mining and Sentiment Analysis”, Foundations and Trends in Information Retrieval 2(1-2), pp. 1–135. 6. Chee Kian Leong, Yew Haur Lee, Wai Keong Mak (2012), “Mining sentiments in SMS texts for teaching evaluation”, Expert Systems with Applications, pp. 2584–2589. 7. Chunxia Yin, Qinke Peng (2009), “Sentiment Analysis for Product Features in Chinese Reviews Based on Semantic Association”, International Conference on Artificial Intelligence and Computational Intelligence, pp.82-85. 8. Fazel Keshtkar, Diana Inkpen (2009), “Using Sentiment Orientation Features for Mood Classification in Blogs”, IEEE, pp. 1-6. 9. Hanxiao Shi, Guodong Zhou, Peide Qian (2010), “An attribute based sentiment analysis system”, Information Technology Journal ISSN 1812-5638, pp.1607-1614. 10. Hong Liu (2010), “Internet public opinion hotspot detection and analysis based on K-means and SVM algorithm”, International Conference of Information Science and Management Engineering, pp.257-261. 11. Huifeng Tang, Songbo Tan, Xueqi Cheng (2009), “A survey on sentiment detection of reviews”, Science Direct Expert Systems with Applications, pp. 10760–10773 12. Hui Wang, Jiansheng Chen (2009), “Extracting Two-Noun Phrases from Customer Reviews”. 13. J. Wiebe, T. Wilson, R. Bruce, M. Bell, and M. Martin(2004), “Learning Subjective Language”, Computational Linguistics, vol. 30, pp. 277–308. 17 14. Jianxiong Wang, Andy Dong (2010),“A Comparison of Two Text Representations for Sentiment Analysis”, in IEEE International Conference on Computer Application and System Modeling (ICCASM 2010), pp.35-39. 15. Khairullah Khan, Baharum B. Baharudin(2012), “Identifying Product Features from Customer Reviews using Lexical Concordance”, Research Journal of Applied Sciences Engineering and Technology 4(7), pp.833-839. 16. Khairullah Khan, Baharum B.Baharudin, Aurangzeb Khan, Fazal-e-Malik (2009),“Mining Opinion from Text Documents: A Survey”, 3rd IEEE International Conference on Digital Ecosystems and Technologies, pp. 217-222. 17. Luole Qi, Li Chen(2011),“Comparison of Model-Based Learning Methods for Feature-Level Opinion Mining”, in IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, pp.265-273 18. M. Hu and B. Liu (2004), “Mining and Summarizing Customer Reviews”, Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 168–177. 19. Magdalini Eirinaki, Shamita Pisal , Japinder Singh (2012),“ Feature-based opinion mining and ranking ”,Journal of Computer and System Sciences ,pp.1175–1184 20. Mani I, Bloedorn E (1997), “Multi-document Summarization by Graph Search and Matching.”, AAAI’97, pp.1-7. 21. Mikalai Tsytsarau, Themis Palpanas (2012), “Survey on mining subjective data on the web”, In Data Min Knowl Disc (2012), pp. 478–514. 22. Mita K. Dalal,Mukesh A. Zave (2011), “Automatic Text Classification: A Technical Review”, International Journal of Computer Applications (0975 – 8887) Volume 28– No.2, pp.37-40, 23. Miqing Hu and Bing Liu (2004) “Mining Opinion Features in Customer Reviews”, American Association for Artificial Intelligence, pp.1-6. 24. N. Jindal and B. Liu (2008), “Opinion Spam and Analysis”, Proceedings of the ACM Conference on Web Search and Data Mining (WSDM), pp.219-229. 25. Rui Xia, Chengqing Zong , Shoushan Li(2011), “Ensemble of feature sets and classification algorithms for sentiment classification ”, ELSEVIER Information Sciences, pp. 1138–1152 26. Xiaowen Ding, Bing Liu, Philip S. Yu (2008), “A Holistic Lexicon-Based Approach to Opinion Mining”, WSDM’08, ACM, pp.1-9. 18 27. Yi Hu, Wenjie Li (2011), “Document sentiment classification by exploring description model of topical terms”, Science Direct Computer Speech and Language, pp. 386–403 28. Yulan He, Deyu Zhou (2011), “Self-training from labeled features for sentiment analysis”, Information Processing and Management, pp. 606–616. 29. Zhixing Li (2010), “Product Feature Extraction with a Combined Approach”, IEEE Third International Symposium on Intelligent Information Technology and Security Informatics, pp.686-690 30. Zhongwu Zhai, Bing Liu, Hua Xu, Peifa Jia (2011), “Clustering Product Features for Opinion Mining”, WSDM’11,ACM,pp.1-8. 19