Finding Correlative Associations among News Topics

  • Authors:

  • Manuel Montes-y-Gómez;Aurelio López-López;Alexander F. Gelbukh

  • Affiliations:

  • -;-;-

  • Venue:
  • CICLing '01 Proceedings of the Second International Conference on Computational Linguistics and Intelligent Text Processing
  • Year:
  • 2001

  • Untangling text data mining

    ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics

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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.