ESUM: An Efficient System for Query-Specific Multi-document Summarization

  • C. Ravindranath Chowdary
  • P. Sreenivasa Kumar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5478)

Abstract

In this paper, we address the problem of generating a query-specific extractive summary in a an efficient manner for a given set of documents. In many of the current solutions, the entire collection of documents is modeled as a single graph which is used for summary generation. Unlike these approaches, in this paper, we model each individual document as a graph and generate a query-specific summary for it. These individual summaries are then intelligently combined to produce the final summary. This approach greatly reduces the computational complexity.

Keywords

Efficient summarization Coherent and Non-redundant summaries 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Salton, G., Singhal, A., Mitra, M., Buckley, C.: Automatic text structuring and summarization. Inf. Process. Manage. 33(2), 193–207 (1997)CrossRefGoogle Scholar
  2. 2.
    Erkan, G., Radev, D.R.: LexPageRank: Prestige in multi-document text summarization. In: Proceedings of EMNLP, Barcelona, Spain, July 2004, pp. 365–371. ACL (2004)Google Scholar
  3. 3.
    Mihalcea, R.: Graph-based ranking algorithms for sentence extraction, applied to text summarization. In: Proceedings of the ACL 2004 on Interactive poster and demonstration sessions, Barcelona, Spain, p. 20. ACL (2004)Google Scholar
  4. 4.
    Otterbacher, J., Erkan, G., Radev, D.R.: Using random walks for question-focused sentence retrieval. In: HLT 2005: Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, Vancouver, British Columbia, Canada, ACL, pp. 915–922. ACL (2005)Google Scholar
  5. 5.
    Carbonell, J.G., Goldstein, J.: The use of mmr, diversity-based reranking for reordering documents and producing summaries. In: SIGIR, Melbourne, Australia, pp. 335–336. ACM, New York (1998)Google Scholar
  6. 6.
    Wang, D., Li, T., Zhu, S., Ding, C.: Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization. In: SIGIR 2008: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, Singapore, pp. 307–314. ACM, New York (2008)Google Scholar
  7. 7.
    Radev, D.R., Jing, H., Budzikowska, M.: Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies. In: NAACL-ANLP 2000 Workshop on Automatic summarization, Seattle, Washington, pp. 21–30. ACL (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • C. Ravindranath Chowdary
    • 1
  • P. Sreenivasa Kumar
    • 1
  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology MadrasChennaiIndia

Personalised recommendations