F. Zamora-Martínez, M. J. Castro-Bleda, S. España-Boquera, Salvador Tortajada, P. Aibar


In this paper, we describe a novel approach to Part-Of-Speech tagging based on neural networks. Multilayer perceptrons are used following corpus-based learning from contextual and lexical information. The Penn Treebank corpus has been used for the training and evaluation of the tagging system. The results show that the connectionist approach is feasible and comparable with other approaches.


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Paper Citation

in Harvard Style

Zamora-Martínez F., J. Castro-Bleda M., España-Boquera S., Tortajada S. and Aibar P. (2009). A CONNECTIONIST APPROACH TO PART-OF-SPEECH TAGGING . In Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009) ISBN 978-989-674-014-6, pages 421-426. DOI: 10.5220/0002313004210426

in Bibtex Style

author={F. Zamora-Martínez and M. J. Castro-Bleda and S. España-Boquera and Salvador Tortajada and P. Aibar},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)},

in EndNote Style

JO - Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)
SN - 978-989-674-014-6
AU - Zamora-Martínez F.
AU - J. Castro-Bleda M.
AU - España-Boquera S.
AU - Tortajada S.
AU - Aibar P.
PY - 2009
SP - 421
EP - 426
DO - 10.5220/0002313004210426