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
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6836)


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.


Semantic Feature Weighted Combination Word Sense Disambiguation Syntactic Feature Lexical Feature 
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 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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