Aspect extraction through semi-supervised modeling

50th Annual Meeting of the Association for Computational Linguistics, ACL 2012 - Proceedings of the Conference

Volumn 1, Issue , 2012, Pages 339-348

  Mukherjee, Arjun ^a   Liu, Bing ^a  

^a 1120 Science and Engineering Offices   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CENTRAL PROBLEMS; SEED WORDS; SEMI-SUPERVISED; SENTIMENT ANALYSIS; TOPIC MODELING; USER GUIDANCE;

COMPUTATIONAL LINGUISTICS; EXTRACTION;

PROBLEM SOLVING;

EID: 84878173804     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (47)

1. Andrzejewski, D., Zhu, X. and Craven, M. 2009. Incorporating domain knowledge into topic modeling via Dirichlet forest priors. Proceedings of International Conference on Machine Learning (ICML).
2. Andrzejewski, D., Zhu, X. and Craven, M. and Recht, B. 2011. A framework for incorporating general domain knowledge into latent Dirichlet allocation using first-order logic. Proceedings of the 22nd International Joint Conferences on Artificial Intelligence (IJCAI).
3. Blair-Goldensohn, S., Hannan, K., McDonald, R., Neylon, T., Reis, G. A. and Reynar, J. 2008. Building a sentiment summarizer for local service reviews. Proceedings of WWW-2008 workshop on NLP in the Information Explosion Era.
4. Blei, D., Ng, A. and Jordan, M. 2003. Latent dirichlet allocation. The Journal of Machine Learning Research 3: 993-1022.
5. Blei D. and McAuliffe, J. 2007. Supervised topic models. Neural Information Processing Systems (NIPS).
6. Branavan, S., Chen, H., Eisenstein, J., and Barzilay, R. 2008. Learning document-level semantic properties from free-text annotations. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL).
7. Brody, S. and Elhadad, S. 2010. An Unsupervised Aspect-Sentiment Model for Online Reviews. Proceedings of The 2010 Annual Conference of the North American Chapter of the ACL (NAACL).
8. Carenini, G., Ng, R. and Zwart, E. 2005. Extracting knowledge from evaluative text. Proceedings of Third Intl. Conf. on Knowledge Capture (K-CAP- 05).
9. Chang, J., Boyd-Graber, J., Wang, C., Gerrish, S., and Blei, D. 2009. Reading tea leaves: How humans interpret topic models. In Neural Information Processing Systems (NIPS).
10. Choi, Y. and Cardie, C. 2010. Hierarchical sequential learning for extracting opinions and their attributes. Proceedings of Annual Meeting of the Association for Computational (ACL).
11. Griffiths, T. and Steyvers, M. 2004. Finding scientific topics. Proceedings of National Academy of Sciences (PNAS).
12. Guo, H., Zhu, H., Guo, Z., Zhang, X. and Su, X. 2009. Product feature categorization with multilevel latent semantic association. Proceedings of ACM International Conference on Information and Knowledge Management (CIKM).
13. Heinrich, G. 2009. A Generic Approach to Topic Models. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD).
14. Hofmann, T. 1999. Probabilistic latent semantic indexing. Proceedings of Conference on Uncertainty in Artificial Intelligence (UAI).
15. Hu, Y., Boyd-Graber, J. and Satinoff, B. 2011. Interactive topic modeling. Proceedings of Annual Meeting of the Association for Computational Linguistics (ACL), 2011.
16. Hu, M. and Liu, B. 2004. Mining and summarizing customer reviews. International Conference on Knowledge Discovery and Data Mining (ICDM).
17. Jakob, N. and Gurevych, I. 2010. Extracting Opinion Targets in a Single-and Cross-Domain Setting with Conditional Random Fields. Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP).
18. Jin, W. and Ho, H. 2009. A novel lexicalized HMMbased learning framework for web opinion mining. Proceedings of International Conference on Machine Learning (ICML).
19. Jo, Y. and Oh, A. 2011. Aspect and sentiment unification model for online review analysis. ACM Conference in Web Search and Data Mining (WSDM).
20. Kobayashi, N., Inui, K. and Matsumoto, K. 2007. Extracting aspect-evaluation and aspect-of relations in opinion mining. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL).
21. Ku, L., Liang, Y. and Chen, H. 2006. Opinion extraction, summarization and tracking in news and blog corpora. Proceedings of AAAI Symposium on Computational Approaches to Analyzing Weblogs (AAAI-CAAW'06).
22. Li, F., Han, C., Huang, M., Zhu, X., Xia, Y., Zhang, S., and Yu, H. 2010. Structure-aware review mining and summarization. International Conference on Computational Linguistics (COLING).
23. Lin, C. and He, Y. 2009. Joint sentiment/topic model for sentiment analysis. Proceedings of ACM International Conference on Information and Knowledge Management (CIKM).
24. Liu, B. 2012. Sentiment Analysis and Opinion Mining. Morgan & Claypool publishers (to appear in June 2012).
25. Liu, B, M. Hu, and J. Cheng. 2005. Opinion Observer: Analyzing and comparing opinions on the web. Proceedings of International Conference on World Wide Web (WWW).
26. Lu, Y., Zhai, C. and Sundaresan, N. 2009. Rated aspect summarization of short comments. Proceedings of International Conference on World Wide Web (WWW).
27. Lu, Y. and Zhai, C. 2008. Opinion Integration Through Semi-supervised Topic Modeling. Proceedings of the 17th International World Wide Web Conference (WWW).
28. Ma, T. and Wan, X. 2010. Opinion target extraction in Chinese news comments. Proceedings of Coling 2010 Poster Volume (COLING).
29. Mei, Q., Ling, X., Wondra, M., Su, H. and Zhai, C. 2007. Topic sentiment mixture: modeling facets and opinions in weblogs. Proceedings of International Conference on World Wide Web (WWW).
30. Moghaddam, S. and Ester, M. 2011. ILDA: interdependent LDA model for learning latent aspects and their ratings from online product reviews. Proceedings of the Annual ACM SIGIR International conference on Research and Development in Information Retrieval (SIGIR).
31. Pang, B. and Lee, L. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval.
32. Popescu, A. and Etzioni, O. 2005. Extracting product features and opinions from reviews. Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP).
33. Qiu, G., Liu, B., Bu, J. and Chen, C. 2011. Opinion Word Expansion and Target Extraction through Double Propagation. Computational Linguistics.
34. Ramage, D., Hall, D., Nallapati, R. and Manning, C. 2009. Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP).
35. Sauper, C., Haghighi, A. and Barzilay, R. 2011. Content models with attitude. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL).
36. Somasundaran, S. and Wiebe, J. 2009. Recognizing stances in online debates, Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP.
37. Teh, Y., Jordan, M., Beal, M. and Blei, D. 2006. Hierarchical Dirichlet Processes. In Journal of the American Statistical Association (JASA).
38. Titov, I. and McDonald, R. 2008. Modeling online reviews with multi-grain topic models. Proceedings of International Conference on World Wide Web (WWW).
39. Wallach, H., Mimno, D. and McCallum, A. 2009. Rethinking LDA: Why priors matter. In Neural Information Processing Systems (NIPS).
40. Wang, H., Lu, Y. and Zhai, C. 2010. Latent aspect rating analysis on review text data: a rating regression approach. Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).
41. Wu, Y., Zhang, Q., Huang, X. and Wu, L. 2009. Phrase dependency parsing for opinion mining. Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP).
42. Yi, J., Nasukawa, T., Bunescu, R. and Niblack, W. 2003. Sentiment analyzer: Extracting sentiments about a given topic using natural language processing techniques. Proceedings of IEEE International Conference on Data Mining (ICDM).
43. Yu, J., Zha, Z. J., Wang, M. and Chua, T. S. 2011. Aspect ranking: identifying important product aspects from online consumer reviews. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics (ACL).
44. Zhai, Z., Liu, B., Xu, H., and Jia, P. 2010. Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints. Proceedings of International Conference on Computational Linguistics (COLING).
45. Zhai, Z., Liu, B., Xu, H., and Jia, P. 2011. Constrained LDA for Grouping Product Features in Opinion Mining. Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD).
46. Zhao, W., Jiang, J., Yan, Y. and Li, X. 2010. Jointly modeling aspects and opinions with a MaxEnt-LDA hybrid. Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP).
47. Zhuang, L., Jing, F. and Zhu, X. 2006. Movie review mining and summarization. Proceedings of International Conference on Information and Knowledge Management (CIKM).