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Automatic Specialized vs. Non-specialized Sentence Differentiation

  • Iria da Cunha
  • M. Teresa Cabré
  • Eric SanJuan
  • Gerardo Sierra
  • Juan Manuel Torres-Moreno
  • Jorge Vivaldi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6609)

Abstract

Compilation of Languages for Specific Purposes (LSP) corpora is a task which is fraught with several difficulties (mainly time and human effort), because it is not easy to discern between specialized and non-specialized text. The aim of this work is to study automatic specialized vs. non-specialized sentence differentiation. The experiments are carried out on two corpora of sentences extracted from specialized and non-specialized texts. One in economics (academic publications and news from newspapers), another about sexuality (academic publications and texts from forums and blogs). First we show the feasibility of the task using a statistical n-gram classifier. Then we show that grammatical features can also be used to classify sentences from the first corpus. For such purpose we use association rule mining.

Keywords

Specialized Text General Text Corpus Languages for Specific Purposes Statistical Methods Association Rules Grammatical features 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Iria da Cunha
    • 2
    • 3
    • 1
  • M. Teresa Cabré
    • 1
  • Eric SanJuan
    • 3
  • Gerardo Sierra
    • 2
  • Juan Manuel Torres-Moreno
    • 2
    • 3
    • 4
  • Jorge Vivaldi
    • 1
  1. 1.Institut Universitari de Linguistique Applicada - UPFBarcelonaEspaña
  2. 2.Grupo de Ingenierá Lingüística - Instituto de Ingeniería UNAM Torre de IngenieríÂa BasamentoCiudad Universitaria MexicoMexico
  3. 3.Laboratoire Informatique d’AvignonUAPVAvignonFrance
  4. 4.Département de génie informatiqueÉcole Polytechnique de MontréalMontréalCanada

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