Finding Correlative Associations among News Topics

  • Manuel Montes-y-Gómez
  • Aurelio López-López
  • Alexander Gelbukh
Conference paper

DOI: 10.1007/3-540-44686-9_53

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2004)
Cite this paper as:
Montes-y-Gómez M., López-López A., Gelbukh A. (2001) Finding Correlative Associations among News Topics. In: Gelbukh A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2001. Lecture Notes in Computer Science, vol 2004. Springer, Berlin, Heidelberg

Abstract

A method for finding real-world associations between news topics (as distinguished from apparent associations caused by the constant size of the newspaper) is described. This is important for studying society interests.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Manuel Montes-y-Gómez
    • 1
  • Aurelio López-López
    • 2
  • Alexander Gelbukh
    • 1
  1. 1.Center for Computing Research (CIC)National Polytechnic Institute (IPN)Mexico
  2. 2.INAOETonantzintlaMéxico

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