An approach based on tree kernels for opinion mining of online product reviews

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2010, Pages 256-265

  Jiang, Peng ^a   Zhang, Chunxia ^a   Fu, Hongping ^a   Niu, Zhendong ^a   Yang, Qing ^a  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Opinion mining; Sentiment analysis; Text mining; Tree kernels

Indexed keywords

BENCHMARK DATA; COMPLEX TASK; DISCUSSION FORUM; FEATURE SELECTION; FEATURE VECTORS; LINEAR COMBINATIONS; MACHINE LEARNING ALGORITHMS; ONLINE PRODUCTS; OPINION MINING; SENTIMENT ANALYSIS; SENTIMENT CLASSIFICATION; SUBTASKS; SYNTACTIC STRUCTURE; TEXT MINING; TREE KERNELS; USER-GENERATED CONTENT;

CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; LEARNING ALGORITHMS; TEXT PROCESSING; TREES (MATHEMATICS);

DATA MINING;

EID: 79951735155     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2010.104     Document Type: Conference Paper

References (34)

1. B. Liu, "Sentiment Analysis and Subjectivity," Handbook of Natural Language Processing, Second Edition, N. Indurkhya, and F.J. Damerau eds., CRC Press, Taylor and Francis Group, 2009.
2. D.T. Peter, "Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews," Proc. Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, Association for Computational Linguistics, 2002, pp. 417 - 424.
3. P. Bo, L. Lillian, and V. Shivakumar, "Thumbs up?: sentiment classification using machine learning techniques," Proc. Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10, Association for Computational Linguistics, 2002, pp. 79 - 86.
4. P. Bo, and L. Lillian, "Opinion Mining and Sentiment Analysis," Found. Trends Inf. Retr. 2008, pp. 1-135.
5. J. Wiebe, T. Wilson, and C. Cardie3, "Annotating Expressions of Opinions and Emotions in Language," Language Resources and Evaluation 2006, pp. 164-210.
6. B. Pang, and L. Lillian, "A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts," Proc. Proceedings of the ACL, Association for Computational Linguistics, 2004, pp. 271-278.
7. T. Mullen, and N. Collier, "Sentiment analysis using support vector machines with diverse information sources," Proceedings of EMNLP 2004, pp. 412-418.
8. Z. Jun, L. Kang, and W. Gen, "Adding redundant features for CRFs-based sentence sentiment classification," Proc. Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing Association for Computational Linguistics, 2008, pp. 117-126.
9. Z. Qi, W. Yuanbin, L. Tao, O. Mitsunori, J. Joseph, and H. Xuanjing, "Mining product reviews based on shallow dependency parsing," Proc. Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, ACM, 2009, pp. 726-727.
10. R. Tokhisa, K. Inui, and Y. Matsumoto, "Emotion Classification Using Massive Examples Extracted from the Web," Proc. Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008), Association for Computational Linguistics, 2008, pp. 881-888.
11. R. Ellen, and W. Janyce, "Learning extraction patterns for subjective expressions," Proc. Proceedings of the 2003 conference on Empirical methods in natural language processing, 2003, pp. 105 - 112.
12. H. Minqing, and L. Bing, "Mining and summarizing customer reviews," Proc. Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, ACM, 2004, pp. 168 - 177.
13. D. Xiaowen, L. Bing, and S.Y. Philip, "A holistic lexicon-based approach to opinion mining," Proc. Proceedings of the international conference on Web search and web data mining, ACM, 2008, pp. 231-240.
14. H. Vasileios, and R.M. Kathleen, "Predicting the semantic orientation of adjectives," Proc. Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics, Association for Computational Linguistics, 1997, pp. 174 - 181.
15. Y. Hong, and H. Vasileios, "Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences," Proc. Proceedings of the 2003 conference on Empirical methods in natural language processing - Volume 10, Association for Computational Linguistics, 2003, pp. 129 - 136.
16. K. Soo-Min, and H. Eduard, "Determining the sentiment of opinions," Proc. Proceedings of the 20th international conference on Computational Linguistics, Association for Computational Linguistics, 2004.
17. P. Ana-Maria, and E. Oren, "Extracting product features and opinions from reviews," Proc. Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2005, pp. 339 - 346.
18. M. Qiaozhu, L. Xu, W. Matthew, S. Hang, and Z. ChengXiang, "Topic sentiment mixture: modeling facets and opinions in weblogs," Proc. Proceedings of the 16th international conference on World Wide Web, ACM, 2007, pp. 171 - 180.
19. L. Wei-Hao, and H. Alexander, "Are these documents written from different perspectives?: a test of different perspectives based on statistical distribution divergence," Proc. Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics, Association for Computational Linguistics, 2006, pp. 1057 - 1064.
20. E. Koji, and L. Victor, "Sentiment retrieval using generative models," Proc. Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2006, pp. 345-354.
21. M. Prem, G. Wojciech, and D.L. Richard, "Sentiment analysis of blogs by combining lexical knowledge with text classification," Proc. Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, ACM, 2009, pp. 1275-1284.
22. I. Titov, and R. McDonald, "A joint model of text and aspect ratings for sentiment summarization," Proc. Proceedings of ACL-08: HLT, Association for Computational Linguistics, 2008, pp. 61801.
23. Z. Min, and Y. Xingyao, "A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval," Proc. Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, ACM, 2008, pp. 411-418.
24. H. Xuanjing, and W.B. Croft, "A unified relevance model for opinion retrieval," Proc. Proceeding of the 18th ACM conference on Information and knowledge management, ACM, 2009, pp. 947-956.
25. A. Ahmed, C. Hsinchun, and S. Arab, "Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums," ACM Trans. Inf. Syst. 2008, pp. 1-34.
26. L. Tao, S. Vikas, D. Chris, and Z. Yi, "Knowledge transformation for cross-domain sentiment classification," Proc. Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, ACM, 2009, pp. 716-717.
27. W. Qiong, T. Songbo, Z. Haijun, Z. Gang, D. Miyi, and C. Xueqi, "SentiRank: Cross-Domain Graph Ranking for Sentiment Classification," Proc. Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, IEEE Computer Society, 2009, pp. 309-314.
28. N. Ramanathan, L. Bing, and C. Alok, "Sentiment analysis of conditional sentences," Proc. Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2009, pp. 180-189
29. G. Murthy, and L. Bing, "Mining opinions in comparative sentences," Proc. Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1, Association for Computational Linguistics, 2008, pp. 241-248.
30. M. Alessandro, P. Daniele, and B. Roberto, "Tree kernels for semantic role labeling," Comput. Linguist. 2008, pp. 193-224.
31. D. Haussler, "Convolution kernels on discrete structures," Technical Report UCSC-CRL-99-10, University of Santa Cruz, 1999.
32. M. Collins, and N. Duffy, "Convolution Kernels for Natural Language," Proceedings of NIPS-2001, 2001.
33. A. Moschitti, "Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees," Proc. In Proceedings of the 17th European Conference on Machine Learning, 2006.
34. W. Theresa, W. Janyce, and H. Paul, "Recognizing contextual polarity in phrase-level sentiment analysis," Proc. Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2005, pp. 347 - 354.