A New Hybrid Summarizer Based on Vector Space Model, Statistical Physics and Linguistics

  • Iria da Cunha
  • Silvia Fernández
  • Patricia Velázquez Morales
  • Jorge Vivaldi
  • Eric SanJuan
  • Juan Manuel Torres-Moreno
Conference paper

DOI: 10.1007/978-3-540-76631-5_83

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4827)
Cite this paper as:
da Cunha I., Fernández S., Velázquez Morales P., Vivaldi J., SanJuan E., Torres-Moreno J.M. (2007) A New Hybrid Summarizer Based on Vector Space Model, Statistical Physics and Linguistics. In: Gelbukh A., Kuri Morales Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science, vol 4827. Springer, Berlin, Heidelberg

Abstract

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Iria da Cunha
    • 1
  • Silvia Fernández
    • 2
    • 4
  • Patricia Velázquez Morales
    • 1
  • Jorge Vivaldi
    • 1
  • Eric SanJuan
    • 2
  • Juan Manuel Torres-Moreno
    • 2
    • 3
  1. 1.Institute for Applied Linguistics, Universitat Pompeu Fabra, Barcelona, Espan̈a 
  2. 2.Laboratoire Informatique d’Avignon, BP1228, 84911 Avignon Cedex 9France
  3. 3.École Polytechnique de Montréal/DGI, Montréal (Québec)Canada
  4. 4.Laboratoire de Physique des Matériaux, CNRS UMR 7556, NancyFrance

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