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Exploration of a Rich Feature Set for Automatic Term Extraction

  • Merley S. Conrado
  • Thiago A. S. Pardo
  • Solange O. Rezende
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8265)

Abstract

Despite the importance of the term extraction methods and that several efforts have been devoted to improve them, they still have 4 main problems: (i) noise and silence generation; (ii) difficulty dealing with high number of terms; (iii) human effort and time to evaluate the terms; and (iv) still limited extraction results. In this paper, we deal with these four major problems in automatic term extraction by exploring a rich feature set in a machine learning approach. We minimized these problems and achieved state of the art results for unigrams in Brazilian Portuguese.

Keywords

Automatic term extraction classification machine learning 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Merley S. Conrado
    • 1
  • Thiago A. S. Pardo
    • 1
  • Solange O. Rezende
    • 1
  1. 1.Instituto de Ciências Matemáticas e de Computação - ICMCUniversidade de São Paulo - Campus de São CarlosSão CarlosBrazil

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