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Extractive Summarization Based on Word Information and Sentence Position

  • Carlos Méndez Cruz
  • Alfonso Medina Urrea
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3406)

Abstract

This paper describes an unsupervised experiment of automatic summarization. The idea is to rate each sentence of a document according to the information content of its graphical words. Also, as a minimal measure of document structure, we added a sentence position coefficient.

Keywords

Information Content Word Type Function Word Source Text Computational Linguistics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Carlos Méndez Cruz
    • 1
  • Alfonso Medina Urrea
    • 1
  1. 1.GIL IINGEN UNAMCoyoacán, DF, Mexico

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