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From single to multi-document summarization: a prototype system and its evaluation

Published: 06 July 2002 Publication History

Abstract

NeATS is a multi-document summarization system that attempts to extract relevant or interesting portions from a set of documents about some topic and present them in coherent order. NeATS is among the best performers in the large scale summarization evaluation DUC 2001.

References

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DUC. 2001. The Document Understanding Workshop 2001. http://www-nlpir.nist.gov/projects/duc/2001.html.
[2]
Dunning, T. 1993. Accurate Methods for the Statistics of Surprise and Coincidence. Computational Linguistics 19, 61--74.
[3]
Edmundson, H. P. 1969. New Methods in Automatic Abstracting. Journal of the Association for Computing Machinery. 16(2).
[4]
Goldstein, J., M. Kantrowitz, V. Mittal, and J. Carbonell. 1999. Summarizing Text Documents: Sentence Selection and Evaluation Metrics. Proceedings of the 22nd International ACM Conference on Research and Development in Information Retrieval (SIGIR-99), Berkeley, CA, 121--128.
[5]
Lin, C.-Y. and E. H. Hovy. 2000. The Automated Acquisition of Topic Signatures for Text Summarization. Proceedings of the COLING Conference. Saarbrücken, Germany.
[6]
Lin, C.-Y. 2001. Summary Evaluation Environment. http://www.isi.edu/~cyl/SEE.
[7]
Luhn, H. P. 1969. The Automatic Creation of Literature Abstracts. IBM Journal of Research and Development 2(2), 1969.
[8]
Mani, I., D. House, G. Klein, L. Hirschman, L. Obrst, T. Firmin, M. Chrzanowski, and B. Sundheim. 1998. The TIPSTER SUMMAC Text Summarization Evaluation: Final Report. MITRE Corp. Tech. Report.
[9]
Mani, I. 2001. Automatic Summarization. John Benjamins Pub Co.
[10]
Marcu, D. 1999. Discourse trees are good indicators of importance in text. In I. Mani and M. Maybury (eds), Advances in Automatic Text Summarization, 123--136. MIT Press.
[11]
Marcu, D. and L. Gerber. 2001. An Inquiry into the Nature of Multidocument Abstracts, Extracts, and their Evaluation. Proceedings of the NAACL -2001 Workshop on Automatic Summarization. Pittsburgh, PA.
[12]
McKeown, K., R. Barzilay, D. Evans, V. Hatzivassiloglou, M-Y Kan, B, Schiffman, and S. Teufel 2001. Columbia Multi-Document Summarization: Approach and Evaluation. DUC-01 Workshop on Text Summarization. New Orleans, LA.
[13]
Radev, D. R. and K. R. McKeown. 1998. Generating Natural Language Summaries from Multiple On-line Sources. Computational Linguistics, 24(3):469--500.

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    ACL '02: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
    July 2002
    543 pages

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    Association for Computational Linguistics

    United States

    Publication History

    Published: 06 July 2002

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