Jade Goldstein
- 1.Proceedings of the A CL 'gV/EA CL '97 Workshop on Intelligent Scalable Text Summarization. Madrid, Spain, 1997.Google Scholar
- 2.Aone, C., Okurowski, M. E., Gorlinsky, J., and Larsen, B. A scalable summarization system using robust NLP. {1}, pp. 66-73.Google Scholar
- 3.Baldwin, B., and Morton, T. S. Dynamic coreferencebased summarization. In Proceedings of the Third Conference on Empirical Methods in Natural Language Processing (EMNLP-3) (Granada, Spain, June 1998).Google Scholar
- 4.Banko, M., Mittal, V., Kantrowitz, M., and Goldstein, J. Generating extraction based summaries from handwritten summaries by aligning text spans. In Proceedings of PACLING-99 (to appear) (Waterloo, Ontario, July 1999).Google Scholar
- 5.Barzilay, R., and Elhadad, M. Using lexical chains for text summarization. {1}, pp. 10-17.Google Scholar
- 6.Boguraev, B., and Kennedy, C. Salience based content characterization of text documents. {1}, pp. 2-9.Google Scholar
- 7.Buckley, C. Implementation of the SMART information retrieval system. Tech. Rep. TR 85-686, Cornell University, 1985. Google ScholarDigital Library
- 8.Carbonell, J. G., and Goldstein, J. The use of MMR, diversity-based reranking for reordering documents and producing summaries. In Proceedings of SIGIR-98 (Melbourne, Australia, Aug. 1998). Google ScholarDigital Library
- 9.Hovy, E., and Lin, C.-Y. Automated text summarization in SUMMARIST. {1}, pp. 18-24. Google ScholarDigital Library
- 10.Jing, H., Barzilay, R., McKeown, K., and Elhadad, M. Summarization evaluation methods experiments and analysis. In AAAI Intelligent Text Summarization Workshop (Stanford, CA, Mar. 1998), pp. 60-68.Google Scholar
- 11.Jones, K. S., and Galliers, J. R. Evaluating Natural Language Processing Systems: an Analysis and Review. Springer, New York, 1996. Google ScholarDigital Library
- 12.Klavans, J. L., and Shaw, J. Lexical semantics in summarization. In Proceedings of the First Annual Workshop of the IFIP Working Group FOR NLP and KR (Nantes, France, Apr. 1995).Google Scholar
- 13.Luhn, P. H. Automatic creation of literature abstracts. IBM Journal (1958), 159-165.Google ScholarDigital Library
- 14.Mani, I., House, D., Klain, G., Hirschman, L., Obrst, L., Firmin, T., Chrzanowski, M., and Sundheim, B. The tipster summac text summarization evaluation. Tech. Rep. MTR 98W0000138, Mitre, October 1998.Google Scholar
- 15.Marcu, D. From discourse structures to text summaries. {1}, pp. 82-88.Google Scholar
- 16.McKeown, K., Robin, J., and Kukich, K. Designing and evaluating a new revision-based model for summary generation. Info. Proc. and Management 31, 5 (1995). Google ScholarDigital Library
- 17.Mitra, M., Singhal, A., and Buckley, C. Automatic text summarization by paragraph extraction. {1}.Google Scholar
- 18.Mittal, V. O., Kantrowitz, M., Goldstein, J., and Carbonell, J. Selecting Text Spans for Document Summaries: Heuristics and Metrics. In Proceedings of AAAI-99 (Orlando, FL, July 1999). Google ScholarDigital Library
- 19.Paice, C. D. Constructing literature abstracts by computer: Techniques and prospects. Info. Proc. and Management 26 (1990), 171-186. Google ScholarDigital Library
- 20.Radev, D., and McKeown, K. Generating natural language summaries from multiple online sources. Computational Linguistics 24, 3 (September 1998), 469-501. Google ScholarDigital Library
- 21.Salton, G., Allan, J., Buckley, C., and Singhal, A. Automatic analysis, theme generation, and summarization of machinereadable texts. Science 264 (1994), 1421-1426.Google ScholarCross Ref
- 22.Salton, G., and Buckley, C. Improving retrieval performance by relevance feedback. Journal of American Society for Information Sciences 41 (1990), 288-297.Google ScholarCross Ref
- 23.Salton, G., and McGill, M. J. Introduction to Modern Information Retrieval. McGraw-Hill Computer Science Series. McGraw-Hill, New York, 1983. Google ScholarDigital Library
- 24.Shaw, J. Conciseness through aggregation in text generation. In Proceedings of 33rd Association for Computational Linguistics (1995), pp. 329-331. Google ScholarDigital Library
- 25.Strzalkowski, T., Wang, J., and Wise, B. A robust practical text summarization system. In AAAI Intelligent Text Summarization Workshop (Stanford, CA, Mar. 1998), pp. 26-30.Google Scholar
- 26.Tait, J. I. Automatic Summarizing of English Texts. PhD thesis, University of Cambridge, Cambridge, UK, 1983.Google Scholar
- 27.Xu, J., and Croft, B. Query expansion using local and global document analysis. In Proceedings of the 19th A CM/SIGIR (SIGIR-96) (1996), ACM, pp. 4-11. Google ScholarDigital Library
Index Terms
- Summarizing text documents: sentence selection and evaluation metrics
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