Question Classification by Weighted Combination of Lexical, Syntactic and Semantic Features

  • Babak Loni
  • Gijs van Tulder
  • Pascal Wiggers
  • David M. J. Tax
  • Marco Loog
Conference paper

DOI: 10.1007/978-3-642-23538-2_31

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6836)
Cite this paper as:
Loni B., van Tulder G., Wiggers P., Tax D.M.J., Loog M. (2011) Question Classification by Weighted Combination of Lexical, Syntactic and Semantic Features. In: Habernal I., Matoušek V. (eds) Text, Speech and Dialogue. TSD 2011. Lecture Notes in Computer Science, vol 6836. Springer, Berlin, Heidelberg

Abstract

We developed a learning-based question classifier for question answering systems. A question classifier tries to predict the entity type of the possible answers to a given question written in natural language. We extracted several lexical, syntactic and semantic features and examined their usefulness for question classification. Furthermore we developed a weighting approach to combine features based on their importance. Our result on the well-known trec questions dataset is competitive with the state-of-the-art on this task.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Babak Loni
    • 1
  • Gijs van Tulder
    • 1
  • Pascal Wiggers
    • 1
  • David M. J. Tax
    • 1
  • Marco Loog
    • 1
  1. 1.Pattern Recognition LaboratoryDelft University of TechnologyDelftThe Netherlands

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