Unsupervised and Semi-Supervised Morphological Analysis for Information Retrieval in the Biomedical Domain

@inproceedings{Claveau2012UnsupervisedAS,
  title={Unsupervised and Semi-Supervised Morphological Analysis for Information Retrieval in the Biomedical Domain},
  author={Vincent Claveau},
  booktitle={COLING},
  year={2012}
}
In the biomedical field, the key to access information is the use of specialized terms. However, in most of Indo-European languages, these terms are complex morphological structures. The aim of the presented work is to identify the various meaningful components of these terms and use this analysis to improve biomedical Information Retrieval. We present an approach combining an automatic alignment using a pivot language, and an analogical learning that allows an accurate morphological analysis… CONTINUE READING
9 Citations
30 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-9 of 9 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 30 references

Eds), Proceedings of the MorphoChallenge 2010

  • M. Kurimo, S. Virpioja, V. T. Turunen
  • Espoo, Finlande.
  • 2010
1 Excerpt

Acquisition morphologique à partir d’un dictionnaire informatisé

  • N. Hathout
  • Actes de la 16e Conférence Annuelle sur le…
  • 2009
1 Excerpt

Similar Papers

Loading similar papers…