Developing learning strategies for topic-based summarization

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2007, Pages 79-86

  Ouyang, You ^a   Li, Sujian ^b   Li, Wenjie ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b PEKING UNIVERSITY   (China)

Author keywords

Document summarization; Support vector regression

Indexed keywords

ASSOCIATED FEATURES; DOCUMENT SETS; DOCUMENT SUMMARIZATION; FEATURE WEIGHTS; LEARNING MODELS; LEARNING STRATEGIES; MANUAL ANNOTATIONS; SUMMARIZATION SYSTEMS; SUPPORT VECTOR REGRESSION; TRAINING DATUM;

COMPETITION; KNOWLEDGE MANAGEMENT; LEARNING SYSTEMS;

REGRESSION ANALYSIS;

EID: 78650422869     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1321440.1321454     Document Type: Conference Paper

References (20)

1. Ani Nenkova and Lucy Vanderwende. The Impact of Frequency on Summarization. MSR-TR-2005-101. Microsoft Research Technical Report, 2005.
2. Chih-Chung Chang and Chih-Jen Lin. LIBSVM: A Library for Support Vector Machines, 2001. http://www.csie.ntu.edu.tw/~cjlin/libsvm
3. Chin-Yew Lin and Eduard Hovy. Manual and Automatic Evaluation of Summaries. In Document Understanding Conference 2002 http:/duc.nist.gov, 2002.
4. Christiane Fellbaum, editer. WordNet: An Electronic Lexical Database. The MIT Press, Cambridge London, 1998.
5. Deepak Ravichandran, Eduard Hovy. Learning Surface Text Patterns for a Question Answering System. In Proceedings of the 40th Annual Meeting of the ACL, pages 41-47, 2002.
6. Dragomir R. Radev, Jahna Otterbacher, Hong Qi, Daniel Tam. MEAD ReDUCs: Michigan at DUC 2003. In Document Understanding Conference 2003, 2003. http://duc.nist.gov
7. Hamish Cunningham, Diana Maynard, Kalina Bontcheva, Valentin Tablan. GATE: A Framework and Graphical Development Environment for Robust NLP Tools and Applications. In Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistics, pages 168-175, 2002.
8. Hoa Trang Dang. Overview of DUC 2005. Document Understanding Conference 2005 http://duc.nist.gov, 2005.
9. Hoa Trang Dang. Overview of DUC 2006. Document Understanding Conference 2006 http://duc.nist.gov, 2006.
10. John M.Conroy, Judith D.Schlesinger, Dianne P.O'Leary. Topic-Focused Multi-document Summarization Using an Approximate Oracle Score. In Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions, pages 152-159, 2006.
11. Julian M. Kupiec, Jan Pedersen, and Francine Chen. A Trainable Document Summarizer. In Edward A. Fox, Peter Ingwersen, and Raya Fidel, editors, Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 68-73, 1995.
12. Liang Zhou and Eduard Hovy. A Web-trained Extraction Summarization System. In Proceedings of HLT-NAACL 2003, pages 205-211, 2003.
13. Lin Zhao, Lide Wu, Xuanjing Huang. Fudan University at DUC 2005. In Document Understanding Conference 2005. http://duc.nist.gov, 2005.
14. Satanjeev Banerjee, Ted Pedersen. An Adapted Lesk Algorithm for Word Sense Disambiguation Using Word Net. In Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing (CICLING-02). pages 136-145, 2002.
15. Schölkopf, B., Bartlett, P. L., Smola, A., & Williamson, R.C. Support Vector Regression with Automatic Accuracy Control. In Proceedings of the 8th International Conference on Artificial Neural Networks, pages 111-116, 1998.
16. Seeger Fisher, Brian Roark. Query-Focused Summarization By Supervised Sentence Ranking and Skewed Word Distributions. In Document Understanding Conference 2006. http:/duc.nist.gov, 2006.
17. Steve R. Gunn. Support Vector Machines for Classification and Regression, Technical Report, Image Speech and Intelligent Systems Research Group, University of
18. Southampton, 1998.
19. Tsutomu Hirao, Hideki Isozaki. Extracting Important Sentences with Support Vector Machines. Proceedings of the 19th International Conference on Computational Linguistics, pages 342-348, 2002.
20. Vladimir Vapnik. Statistical Learning Theory. John Wiley and Sons, New York, 1998.