Identifying comparative sentences in text documents

Proceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn 2006, Issue , 2006, Pages 244-251

  Jindal, Nitin ^a   Liu, Bing ^a  

^a University of Illinois at Chicago   (United States)

Author keywords

Comparative sentences; Sentiment classification; Text mining

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPACT DISK PLAYERS; DATA MINING; INTERNET; PROBLEM SOLVING; COMPETITIVE INTELLIGENCE; ELECTRONIC DOCUMENT IDENTIFICATION SYSTEMS; PATTERN RECOGNITION;

COMPARATIVE SENTENCES; OPINION IDENTIFICATION; SENTIMENT CLASSIFICATION; TEXT MINING; INTEGRATED PATTERNS; SENTIMENT CLASSIFICATIONS; TEXT MININGS;

TEXT PROCESSING; INFORMATION RETRIEVAL SYSTEMS;

EID: 33750308486     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1148170.1148215     Document Type: Conference Paper

References (35)

1. Agrawal, R. Srikant, R. Mining sequential patterns. ICDE'94, 1994.
2. Ayres, J., Flannick, J., Gehrke, J., Yiu, T. Sequential pattern mining using a bitmap representation. KDD '02
3. Brill, E. A simple rule-based part of speech tagger. ANL, 1992.
4. Das, S. and Chen, M., Yahoo! for Amazon: Extracting market sentiment from stock message boards. APFA, 2001.
5. Dave, K., Lawrence, S., and Pennock, D. Mining the Peanut Gallery: Opinion extraction and semantic classification of product reviews. WWW'03, 2003.
6. Doran, C., Egedi, D., Hockey, B. A., Srinivas, B., Zaidel, M. XTAG System-A wide coverage grammar for English. COLING'94, 1994.
7. Fellbaum, C. WordNet: an electronic lexical database, MIT Press, 1998.
8. Carenini, G. Ng, R., Zwart, E. Extracting knowledge from evaluative text. ICKC'05, 2005.
9. Hatzivassiloglou, V., and Wiebe, J. Effects of adjective orientation and gradability on sentence subjectivity. COLING'00, 2000.
10. Hearst, M., Direction-based text interpretation as an information access refinement. In P. Jacobs, editor, Text-Based Intelligent Systems. Lawrence Erlbaum Assoc., 1992.
11. Hu, M., and Liu, B. Mining and summarizing customer reviews. KDD '04, 2004.
12. Jindal, N., and Liu, B. Mining comparative sentences and relations. AAAI'06, 2006
13. Joachims, T. Making large-scale SVM learning practical. Advances in Kernel Methods - Support Vector Learning, B. Schölkopf and C. Burges and A. Smola (ed.), 1999.
14. Kennedy, C. Comparatives, semantics of. In Enclycopedia of Language and Linguistics, Second Edition, Elsevier, 2005.
15. Kobayashi, N., Iida, R., Inui, K. and Matsumoto, Y. Opinion mining on the Web by extracting subject-attribute-value relations. AAAI-CAAW'06, 2006.
16. Ku, L-W., Liang, Y-T. and Chen, H-H. Opinion extraction, summarization and tracking in news and blog corpora. AAAI-CAAW'06, 2006.
17. Lerner, J. and Pinkal M. Comparatives and nested quantification. CLAUS-Report 21, 1992.
18. Liu, B., Hsu, W. and Ma, Y. Mining association rules with multiple minimum supports. KDD'99, 1999.
19. Liu, B., Hu, M. and Cheng, J. Opinion observer: analyzing and comparing opinions on the Web. WWW'05, 2005.
20. Liu, B. Web Data Mining: Exploring hyperlinks, Contents, and Usage Data. A forthcoming book. 2006/2007.
21. Mitchell, T. Machine learning, McGraw-Hill, 1997.
22. Moltmann, F., Coordination and comparatives. Ph.D. dissertation. MIT, Cambridge Ma., 1987.
23. Nasukawa, T. and Yi, J. Sentiment analysis: Capturing favorability using natural language processing. K-CA, 2003.
24. Pang, B., Lee, L., and Vaithyanathan, S., Thumbs up? Sentiment Classification Using Machine Learning Techniques. EMNLP'02, 2002.
25. Pei, J. Han, J., Mortazavi-Asl, B., Wang, J., Pinto, H., Chen, Q., Dayal, U., and Hsu, M.-C. Mining sequential patterns by Pattern-Growth: The PrefixSpan approach. IEEE Trans. on Knowl. and Data Engineering, 16(10), 2004.
26. Popescu, A-M and Etzioni. O. Extracting product features and opinions from reviews. EMNLP-05, 2005.
27. Riloff, E. and Wiebe, J. Learning extraction patterns for subjective expressions. EMNLP '03, 2003.
28. Santorini, B., Part-of-Speech tagging guidelines for the Penn Treebank project. Technical report MS-CIS-90-47. U. Pennsylvania. Dep't. Of Computer Science, 1990.
29. Tong, R. An operational system for detecting and tracking opinions in on-line discussions. SIGIR 2001 Workshop on Operational Text Classification, 2001.
30. Turney, P. 2002. Thumbs up or Thumbs down? Semantic orientation applied to unsupervised classification of reviews. ACL '02, 2002.
31. Vapnik. V. The nature of statistical learning theory, Springer, 1995.
32. Wiebe, J., Bruce, R., and O'Hara, T. Development and use of a gold standard data set for subjectivity classifications. ACL'99, 1999.
33. Wilson, T., Wiebe, J., and Hwa, R. Just how mad are you? Finding strong and weak opinion clauses. AAAI'04, 2004.
34. Yu, H., and Hatzivassiloglou, V. Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. EMNLP '03, 2003.
35. Zhai, C, Velivelli, A., and Yu, B. A cross-collection mixture model for comparative text mining, KDD '04, 2004.