Extrinsic evaluation on automatic summarization tasks: testing affixality measurements for statistical word stemming

  • Authors:
  • Carlos-Francisco Méndez-Cruz;Juan-Manuel Torres-Moreno;Alfonso Medina-Urrea;Gerardo Sierra

  • Affiliations:
  • LIA-Université d'Avignon et des Pays de Vaucluse, France,GIL-Instituto de Ingeniería UNAM, México;LIA-Université d'Avignon et des Pays de Vaucluse, France,École Polytechnique de Montréal, Canada;El Colegio de México A.C., México;GIL-Instituto de Ingeniería UNAM, México

  • Venue:
  • MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
  • Year:
  • 2012

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Abstract

This paper presents some experiments of evaluation of a statistical stemming algorithm based on morphological segmentation. The method estimates affixality of word fragments. It combines three indexes associated to possible cuts. This unsupervised and language-independent method has been easily adapted to generate an effective morphological stemmer. This stemmer has been coupled with Cortex, an automatic summarization system, in order to generate summaries in English, Spanish and French. Summaries have been evaluated using ROUGE. The results of this extrinsic evaluation show that our stemming algorithm outperforms several classical systems.