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A Lexicographic Encoding for Word Sense Disambiguation with Evolutionary Neural Networks

  • A. Azzini
  • C. da Costa Pereira
  • M. Dragoni
  • A. G. B. Tettamanzi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5883)

Abstract

We propose a supervised approach to word sense disambiguation based on neural networks combined with evolutionary algorithms. Large tagged datasets for every sense of a polysemous word are considered, and used to evolve an optimized neural network that correctly disambiguates the sense of the given word considering the context in which it occurs.

A new distributed scheme based on a lexicographic encoding to represent the context in which a particular word occurs is proposed.

The viability of the approach has been demonstrated through experiments carried out on a representative set of polysemous words.

Keywords

Target Word Word Sense Confusion Matrice Word Sense Disambiguation Supervise Approach 
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 2009

Authors and Affiliations

  • A. Azzini
    • 1
  • C. da Costa Pereira
    • 1
  • M. Dragoni
    • 1
  • A. G. B. Tettamanzi
    • 1
  1. 1.Dipartimento di Tecnologie dell’InformazioneUniversità degli Studi di MilanoCremaItaly

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