A part-of-speech lexicographic encoding for an evolutionary word sense disambiguation approach

  • Authors:

  • Antonia Azzini;Mauro Dragoni;Andrea G. B. Tettamanzi

  • Affiliations:

  • Universita' degli Studi di Milano, Dipartimento di Tecnologie dell'Informazione;Universita' degli Studi di Milano, Dipartimento di Tecnologie dell'Informazione;Universita' degli Studi di Milano, Dipartimento di Tecnologie dell'Informazione

  • Venue:
  • EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
  • Year:
  • 2011

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Abstract

This work proposes a novel distributed scheme based on a part-of-speech tagged lexicographic encoding to represent the context in which a particular word occurs in an evolutionary approach for word sense disambiguation. Tagged dataset for every sense of a polysemous word are considered as inputs to supervised classifiers, Artificial Neural Networks (ANNs), which are evolved by a joint optimization of their structures and weights, together with a similarity based recombination operator. The viability of the approach has been demonstrated through experiments carried out on a representative set of polysemous words. Comparison with the best entries of the Semeval-2007 competition has shown that the proposed approach is competitive with state-of-the-art WSD approaches.