A semi-supervised approach to question classification

@inproceedings{Toms2009ASA,
  title={A semi-supervised approach to question classification},
  author={David Tom{\'a}s and Claudio Giuliano},
  booktitle={ESANN},
  year={2009}
}
This paper presents a machine learning approach to question classification. We have defined a kernel function based on latent semantic information acquired from unlabeled data. This kernel allows including external semantic knowledge into the supervised learning process. We have combined this knowledge with a bag-of-words approach by means of composite kernels to obtain state-of-the-art results. As the semantic information is acquired from unlabeled text, our system can be easily adapted to… CONTINUE READING

Citations

Publications citing this paper.

References

Publications referenced by this paper.
Showing 1-8 of 8 references

Indexing by latent semantic analysis

  • Scott C. Deerwester, Susan T. Dumais, Thoms K. Landauer, George W. Furnas, Richard A. Harshman
  • Journal of the American Society of Information…
  • 1990

Computer-Intensive Methods for Testing Hypotheses

  • Eric W. Noreen
  • 1989
1 Excerpt

Similar Papers

Loading similar papers…