A generic sentence trimmer with CRFs

ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

Volumn , Issue , 2008, Pages 299-307

  Nomoto, Tadashi ^a  

^a National Institutes for the Humanities   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CONDITIONAL RANDOM FIELDS (CRFS); GENERIC TREE;

COMPUTATIONAL LINGUISTICS;

EID: 77953251325     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. James Clarke and Mirella Lapata. 2006. Constraintbased sentence compression: An integer programming approach. In Proceedings of the COLING/ACL 2006, pages 144-151.
2. Trevor Cohn and Mirella Lapata. 2007. Large margin synchronous generation and its application to sentence compression. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 73-82, Prague, June.
3. Bonnie Dorr, David Zajic, and Richard Schwartz. 2003. Hedge trimmer: A parse-and-trim approach to headline generataion. In Proceedings of the HLT-NAACL Text Summarization Workshop and Document Understanding Conderence (DUC03), pages 1-8, Edmonton, Canada.
4. Satoshi Fukutomi, Kazuyuki Takagi, and Kazuhiko Ozeki. 2007. Japanese Sentence Compression using Probabilistic Approach. In Proceedings of the 13th Annual Meeting of the Association for Natural Language Processing Japan.
5. Michel Galley and Kathleen McKeown. 2007. Lexicalized Markov grammars for sentence compression. In Proceedings of the HLT-NAACL 2007, pages 180-187.
6. Hongyan Jing. 2000. Sentence reduction for automatic text summarization. In Proceedings of the 6th Conference on Applied Natural Language Processing, pages 310-315.
7. Tomonori Kikuchi, Sadaoki Furui, and Chiori Hori. 2003. Two-stage automatic speech summarization by sentence extraction and compaction. In Proceedings of ICASSP 2003.
8. Kevin Knight and Daniel Marcu. 2002. Summarization beyond sentence extraction: A probabilistic approach to sentence compression. Artificial Intelligence, 139:91-107.
9. John Lafferty, Andrew MacCallum, and Fernando Pereira. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of the 18th International Conference on Machine Learning (ICML-2001).
10. Ryan McDonald. 2006. Discriminative sentence compression with soft syntactic evidence. In Proceedings of the 11th Conference of EACL, pages 297-304.
11. Yuhei Morooka, Makoto Esaki, Kazuyuki Takagi, and Kazuhiko Ozeki. 2004. Automatic summarization of news articles using sentence compaction and extraction. In Proceedings of the 10th Annual Meeting of Natural Language Processing, pages 436-439, March. (In Japanese).
12. Tadashi Nomoto. 2007. Discriminative sentence compression with conditional random fields. Information Processing and Management, 43:1571 - 1587.
13. Rei Oguro, Kazuhiko Ozeki, Yujie Zhang, and Kazuyuki Takagi. 2000. An efficient algorithm for Japanese sentence compaction based on phrase importance and inter-phrase dependency. In Proceedings of TSD 2000 (Lecture Notes in Artificial Intelligence 1902, Springer-Verlag), pages 65-81, Brno, Czech Republic.
14. Stefan Riezler, Tracy H. King, Richard Crouch, and Annie Zaenen. 2003. Statistical sentence condensation using ambiguity packing and stochastic disambiguation methods for lexical functional grammar. In Proceedings of HLT-NAACL 2003, pages 118-125, Edmonton.
15. Dan Roth and Wen-tau Yih. 2005. Integer linear programming inference for conditional random fields. In Proceedings of the 22nd International Conference on Machine Learning (ICML 05).
16. T. F. Smith and M. S. Waterman. 1981. Identification of common molecular subsequence. Journal of Molecular Biology, 147:195-197.
17. Charles Sutton and Andrew McCallum. 2006. An introduction to conditional random fields for relational learning. In Lise Getoor and Ben Taskar, editors, Introduction to Statistical Relational Learning. MIT Press. To appear.
18. Charles Sutton, Khashayar Rohanimanesh, and Andrew McCallum. 2004. Dynamic conditional random fields: Factorized probabilistic labeling and segmenting sequence data. In Proceedings of the 21st International Conference on Machine Learning, Banff, Canada.
19. Charles Sutton. 2006. GRMM: A graphical models toolkit. http://mallet.cs.umass.edu.
20. Ben Tasker. 2004. Learning Structured Prediction Models: A Large Margin Approach. Ph.D. thesis, Stanford University.
21. Roy W. Tromble and Jason Eisner. 2006. A fast finitestate relaxation method for enforcing global constraint on sequence decoding. In Proceeings of the NAACL, pages 423-430.
22. Jenie Turner and Eugen Charniak. 2005. Supervised and unsupervised learning for sentence compression. In Proceedings of the 43rd Annual Meeting of the ACL, pages 290-297, Ann Arbor, June.
23. Vincent Vandeghinste and Yi Pan. 2004. Sentence compression for automatic subtitling: A hybrid approach. In Proceedings of the ACL workshop on Text Summarization, Barcelona.
24. Kiwamu Yamagata, Satoshi Fukutomi, Kazuyuki Takagi, and Kzauhiko Ozeki. 2006. Sentence compression using statistical information about dependency path length. In Proceedings of TSD 2006 (Lecture Notes in Computer Science, Vol. 4188/2006), pages 127-134, Brno, Czech Republic.