Skip to main content

Text Summarization

  • Living reference work entry
  • Latest version View entry history
  • First Online:
  • 55 Accesses

Synonyms

Document summarization

Definition

Text summarization is the process of distilling the most important information from a text to produce an abridged version for a particular task and user [9].

Historical Background

With more and more digitalized text being available, especially with the development of the Internet, people are being overwhelmed with data. How to help people effectively and efficiently capture the information from the data becomes extremely important. Many techniques have been proposed for this goal and text summarization is one of them.

Text summarization in some form has been in existence since the 1950s [8]. Two main influences have dominated the research in this area, as summarized by Mani in [10]. Work in library science, office automation, and information retrieval has resulted in a focus on methods for producing extracts from scientific papers, including the use of “shallow” linguistic analysis and the use of term statistics. The other influence has been...

This is a preview of subscription content, log in via an institution.

Recommended Reading

  1. Berry MW, Dumais ST, O’Brien GW. Using linear algebra for intelligent information retrieval. SIAM Rev. 1995;37(4):573–95.

    Article  MathSciNet  MATH  Google Scholar 

  2. Brandowa R, Mitzeb K, Rauc LF. Automatic condensation of electronic publications by sentence selection. Inform Process Manage. 1995;41(6):675–85.

    Article  Google Scholar 

  3. Conroy JM, O’leary DP. Text summarization via hidden markov models. In: Proceedings of the 24th annual international ACM SIGIR conference on research and development in information retrieval. 2001. p. 406–7.

    Google Scholar 

  4. Goldstein J, Kantrowitz M, Mittal V, Carbonell J. Summarizing text documents: sentence selection and evaluation metrics. In: Proceedings of the 22nd annual international ACM SIGIR conference on research and development in information retrieval. 1999. p. 121–8.

    Google Scholar 

  5. Gong Y, Liu X. Generic text summarization using relevance measure and latent semantic analysis. In: Proceedings of the 24th annual international ACM SIGIR conference on research and development in information retrieval. 2001. p. 19–25.

    Google Scholar 

  6. 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. 1995. p. 68–73.

    Google Scholar 

  7. Lin C-Y, Hovy E. Automatic evaluation of summaries using n-gram co-occurrence statistics. In: Proceedings of the human language technology conference of the North American Chapter of Association Computational Linguistics. 2003. p. 71–8.

    Google Scholar 

  8. Luhn HP. The automatic creation of literature abstracts. IBM J Res Dev. 1958;2(2):159–65.

    Article  MathSciNet  Google Scholar 

  9. Mani I. Advances in automatic text summarization. Cambridge: MIT; 1999.

    Google Scholar 

  10. Mani I. Recent developments in text summarization. In: Proceedings of the 10th international conference on information and knowledge management. 2001 p. 529–31.

    Google Scholar 

  11. Marcu D. From discourse structures to text summaries. In: Proceedings of the ACL workshop on intelligent scalable text summarization. 1997. p. 82–8.

    Google Scholar 

  12. Mihalcea R. Language independent extractive summarization. In: Proceedings of the 20th national conference on AI and 17th innovative applications of AI conference. 2005. p. 1688–9.

    Google Scholar 

  13. Shen D, Chen Z, Yang Q, Zeng H-J, Zhang B, Lu Y, Ma W-Y. Web-page classification through summarization. In: Proceedings of the 30th annual international ACM SIGIR conference on research and development in information retrieval. 2004. p. 242–9.

    Google Scholar 

  14. Shen D, Sun J-T, Li H, Yang Q, Chen Z. Document summarization using conditional random fields. In: Proceedings of the 20th international joint conference on AI. 2007. p. 2862–7.

    Google Scholar 

  15. Teufel S, Moens M. Sentence extraction as a classification task. In: Proceedings of the ACL workshop on intelligent text summarization. 1997. p. 58–65.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dou Shen .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media LLC

About this entry

Cite this entry

Shen, D. (2017). Text Summarization. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_424-3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_424-3

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4899-7993-3

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Chapter history

  1. Latest

    Text Summarization
    Published:
    13 February 2017

    DOI: https://doi.org/10.1007/978-1-4899-7993-3_424-3

  2. Original

    Text Summarization
    Published:
    27 December 2016

    DOI: https://doi.org/10.1007/978-1-4899-7993-3_424-2