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Extracting Multi-document Summaries with a Double Clustering Approach

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Natural Language Processing and Information Systems (NLDB 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7337))

Abstract

This paper presents a method for extractive multi-document summarization that explores a two-phase clustering approach. First, sentences are clustered by similarity, and one sentence per cluster is selected, to reduce redundancy. Then, in order to group them according to topics, those sentences are clustered considering the collection of keywords. Additionally, the summarization process further includes a sentence simplification step, which aims not only to create simpler and more incisive sentences, but also to make room for the inclusion of relevant content in the summary as much as possible.

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References

  1. Aleixo, P., Pardo, T.A.S.: Cstnews: Um córpus de textos jornalísticos anotados segundo a teoria discursiva multidocumento cst (cross-document structure theory). Tech. rep., Universidade de São Paulo (2008)

    Google Scholar 

  2. Branco, A., Silva, J.: A suite of shallow processing tools for portuguese: Lx-suite. In: Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2006 (2006)

    Google Scholar 

  3. Carbonell, J.G., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: Research and Development in Information Retrieval, pp. 335–336 (1998)

    Google Scholar 

  4. Dice, L.R.: Measures of the amount of ecologic association between species. Ecology 26(3), 297–302 (1945)

    Article  Google Scholar 

  5. Edmundson, H.P.: New methods in automatic extracting. J. ACM 16(2), 264–285 (1969)

    Article  MATH  Google Scholar 

  6. Jaccard, P.: Nouvelles recherches sur la distribution florale. Bulletin de la Sociète Vaudense des Sciences Naturelles 44, 223–270 (1908)

    Google Scholar 

  7. Lin, C.Y.: Rouge: A package for automatic evaluation of summaries. In: Marie-Francine Moens, S.S. (ed.) Text Summarization Branches Out: Proceedings of the ACL 2004 Workshop, pp. 74–81. ACL, Barcelona (2004)

    Google Scholar 

  8. Lin, C.Y., Hovy, E.: From single to multi-document summarization: A prototype system and its evaluation. In: Proceedings of the ACL, pp. 457–464. MIT Press (2002)

    Google Scholar 

  9. Luhn, H.P.: The automatic creation of literature abstracts. IBM Journal of Research and Development 2 (1958)

    Google Scholar 

  10. MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press (1967)

    Google Scholar 

  11. Mani, I.: Automatic Summarization. Benjamins Pub. Co., Amsterdam (2001)

    Google Scholar 

  12. Pardo, T.A.S., Rino, L.H.M., das Graças Volpe Nunes, M.: GistSumm: A Summarization Tool Based on a New Extractive Method. In: Mamede, N.J., Baptista, J., Trancoso, I., Nunes, M.d.G.V. (eds.) PROPOR 2003. LNCS, vol. 2721, pp. 210–218. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  13. Radev, D.R., Jing, H., Budzikowska, M.: Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies. In: Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization, NAACL-ANLP-AutoSum 2000, pp. 21–30. ACL (2000)

    Google Scholar 

  14. Silva, J., Branco, A., Castro, S., Reis, R.: Out-of-the-Box Robust Parsing of Portuguese. In: Pardo, T.A.S., Branco, A., Klautau, A., Vieira, R., de Lima, V.L.S. (eds.) PROPOR 2010. LNCS, vol. 6001, pp. 75–85. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  15. White, M., Korelsky, T., Cardie, C., Ng, V., Pierce, D., Wagstaff, K.: Multidocument summarization via information extraction. In: HLT 2001: Proceedings of the First International Conference on Human Language Technology Research, pp. 1–7 (2001)

    Google Scholar 

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Author information

Authors and Affiliations

  1. University of Lisbon, Portugal

    Sara Botelho Silveira & António Branco

  2. Edifício C6, Departamento de Informática Faculdade de Ciências, Universidade de Lisboa Campo Grande, 1749-016, Lisboa, Portugal

    Sara Botelho Silveira & António Branco

Authors
  1. Sara Botelho Silveira
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  2. António Branco
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Editor information

Editors and Affiliations

  1. Information Science Department, University of Groningen, Oude Kijk in ’t Jatstraat 26, 9712 EK, Groningen, The Netherlands

    Gosse Bouma

  2. Faculty of Economics and Business, University of Groningen, Nettelbosje 2, 9747 AE, Groningen, The Netherlands

    Ashwin Ittoo  & Hans Wortmann  & 

  3. CNAM-Laboratoire Cédric, 292 rue St. Martin, 75141, Paris Cedex 03, France

    Elisabeth Métais

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© 2012 Springer-Verlag Berlin Heidelberg

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Silveira, S.B., Branco, A. (2012). Extracting Multi-document Summaries with a Double Clustering Approach. In: Bouma, G., Ittoo, A., Métais, E., Wortmann, H. (eds) Natural Language Processing and Information Systems. NLDB 2012. Lecture Notes in Computer Science, vol 7337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31178-9_7

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  • DOI: https://doi.org/10.1007/978-3-642-31178-9_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31177-2

  • Online ISBN: 978-3-642-31178-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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