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Using Question-Answer Pairs in Extractive Summarization of Email Conversations

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Computational Linguistics and Intelligent Text Processing (CICLing 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4394))

Abstract

While sentence extraction as an approach to summarization has been shown to work in documents of certain genres, because of the conversational nature of email communication, sentence extraction may not result in a coherent summary. In this paper, we present our work on augmenting extractive summaries of threads of email conversations with automatically detected question-answer pairs. We compare various approaches to integrating question-answer pairs in the extractive summaries, and show that their use improves the quality of email summaries.

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References

  1. Nenkova, A., Schiffman, B., Schlaiker, A., Blair-Goldensohn, S., Barzilay, R., Sigelman, S., Hatzivassiloglou, V., McKeown, K.: Columbia university at duc 2003. In: 3rd Document Understanding Conference 2003 (DUC 2003) (2003)

    Google Scholar 

  2. Blair-Goldensohn, S., Evans, D., Hatzivassiloglou, V., McKeown, K., Nenkova, A., Passonneau, R., Schiffman, B., Schlaikjer, A., Siddharthan, A., Siegelman, S.: Columbia university at duc 2004. In: 4th Document Understanding Conference 2004 (DUC 2004) (2004)

    Google Scholar 

  3. Kupiec, J., Pedersen, J., Chen, F.: A trainable document summarizer. In: Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR’95, Seattle, WA, ACM Press, New York (1995)

    Google Scholar 

  4. Rambow, O., Shrestha, L., Chen, J., Lauridsen, C.: Summarizing email threads. In: Proceedings of HLT-NAACL 2004 Short, Boston, USA (2004)

    Google Scholar 

  5. Shrestha, L., McKeown, K.: Detection of question-answer pairs in email conversations. In: Proceedings of the 20th International Conference on Computational Linguistics (COLING 2004), Geneva, Switzerland (2004)

    Google Scholar 

  6. Zechner, K.: Automatic summarization of open-domain multiparty dialogues in diverse genres. Computational Linguistics 28(4), 447–485 (2002)

    Article  Google Scholar 

  7. Muresan, S., Tzoukermann, E., Klavans, J.: Combining Linguistic and Machine Learning Techniques for Email Summarization. In: Proceedings of the CoNLL 2001 Workshop at the ACL/EACL 2001 Conference (2001)

    Google Scholar 

  8. Lam, D., Rohall, S.L., Schmandt, C., Stern, M.K.: Exploiting e-mail structure to improve summarization. In: ACM 2002 Conference on Computer Supported Cooperative Work (CSCW2002), Interactive Posters, New Orleans, LA, ACM Press, New York (2002)

    Google Scholar 

  9. Newman, P., Blitzer, J.: Summarizing archived discussions: a beginning. In: Proceedings of Intelligent User Interfaces (2003)

    Google Scholar 

  10. Dalli, A., Xia, Y., Wilks, Y.: Fasil email summarisation system. In: Proceedings of the 20th International Conference on Computational Linguistics (COLING 2004), Geneva, Switzerland (2004)

    Google Scholar 

  11. Nenkova, A., Bagga, A.: Facilitating email thread access by extractive summary generation. In: Proceedings of RANLP, Bulgaria (2003)

    Google Scholar 

  12. Hatzivassiloglou, V., Klavans, J., Holcombe, M., Barzilay, R., Kan, M.-Y., McKeown, K.: SimFinder: A flexible clustering tool for summarization. In: Proceedings of the NAACL Workshop on Automatic Summarization, Pittsburgh, PA (2001)

    Google Scholar 

  13. Cohen, W.: Learning trees and rules with set-valued features. In: Fourteenth Conference of the American Association of Artificial Intelligence, AAAI Press, Menlo Park (1996)

    Google Scholar 

  14. Carletta, J.: Assessing agreement on classification tasks: The kappa statistic. Computational Linguistics 22(2), 249–254 (1996)

    Google Scholar 

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Alexander Gelbukh

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© 2007 Springer-Verlag Berlin Heidelberg

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McKeown, K., Shrestha, L., Rambow, O. (2007). Using Question-Answer Pairs in Extractive Summarization of Email Conversations. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2007. Lecture Notes in Computer Science, vol 4394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70939-8_48

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  • DOI: https://doi.org/10.1007/978-3-540-70939-8_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70938-1

  • Online ISBN: 978-3-540-70939-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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