WANN-TAGGER - A Weightless Artificial Neural Network Tagger for the Portuguese Language

Hugo C. C. Carneiro, Felipe M. G. França, Priscila M. V. Lima

Abstract

Weightless Artificial Neural Networks have proved to be a promising paradigm for classification tasks. This work introduces the WANN-Tagger, which makes use of weightless artificial neural networks for labelling Portuguese sentences, tagging each of its terms with its respective part-of-speech. A first experimental evaluation using the CETENFolha corpus indicates the usefulness of this paradigm and shows that it outperforms traditional feedforward neural networks in both accuracy and training time, and also that it is competitive in accuracy with the Hidden Markov Model in some cases. Additionally, WANN-Tagger shows itself capable of incrementally learning new tagged sentences during runtime.

References

  1. Alexander, I., Thomas, W. V., Bowden, P. A., 1984. WiSARD: a radical step forward in image recognition. In Sensor Review, pp. 120-124.
  2. Alexander, I., Kan, W. W., 1987. A probabilistic logic neuron network for associative learning. In IEEE Proceedings of the First International Conference on Neural Networks, pp. 541-548.
  3. Alexander, I., 1990. Ideal neurons for neural computers. In Parallel Processing in Neural Systems and Computers, North-Holland, Amsterdam, pp. 225-228.
  4. Alexander, I., Morton, H., 1991. General neural unit: retrieval performance. In IEE Electronics Letters, 27, pp. 1176-1178.
  5. Alias-i, 2009. LingPipe 3.9.2 http://alias-i.com/lingpipe (accessed October 1, 2009).
  6. Baum, L. E., 1972. An inequality and associated maximization technique in statistical estimation for probabilistic functions of Markov processes. In Shinsha, O. (Ed.), Inequalities III: Proceedings of the 3rd Symposium on Inequalities, University of California, Los Angeles, pp. 1-8. Academic Press.
  7. Bick, E., 2000. The Parsing System Palavras - Automatic Grammatical Analysis of Portuguese in a Constraint Grammar Framework. Århus University Press.
  8. Brill, E., 1995. Transformation-based error-driven learning and natural language processing: a case study in part-of-speech tagging. In Computational Linguistics, 21(4), pp. 543-566.
  9. Carvalho Filho, E. C. B., Fairhurst, M. C., Bisset, D. L., 1991. Adaptive pattern recognition using goal-seeking neurons. In Pattern Recognition Letters, 12, pp. 131- 138.
  10. Dempster, A. P., Laird, N. M., Rubin, D. B., 1977. Maximum likelihood from incomplete data via the EM algorithm. In Journal of the Royal Statistical Society, 39(1), pp 1-21.
  11. Francis, W. N., Kucera, H. (1982). Frequency Analysis of English Usage. Houghton Mifflin, Boston.
  12. Grieco, B. P. A., Lima, P. M. V., De Gregorio, M., França, F. M. G., 2010. Producing pattern examples from “mental” images. In Neurocomputing, 73, pp. 1057- 1064.
  13. Kanerva, P., 1988. Sparse Distributed Memory. MIT Press.
  14. Karlsson, F., Vuotilainen, A., Heikkilä, J., Anttila, A., 1995. Constraint Grammar: A Language-Independent System for Parsing Unrestricted Text. Mouton de Gruyter.
  15. Lafferty, J., McCallum, A., Pereira, F., 2001. Conditional random fields: probabilistic models for segmenting and labeling sequence data. In Proceedings of the 18th International Conference on Machine Learning.
  16. Linguateca, 2009. CETENFolha http://www.linguateca.pt/ CETENFolha/index_info.html (accessed October 1, 2009).
  17. Marques, N. C., Lopes, G. P., 1996. Using neural nets for portuguese part-of-speech tagging. In Proceedings of the 5th International Conference on the Cognitive Science of Natural Language Processing.
  18. McCallum, A., Freitag, D., Pereira, F., 2000. Maximum entropy Markov models for information extraction and segmentation. In Proceedings of the 17th International Conference on Machine Learning.
  19. Rabiner, L. R., 1989. A tutorial on hidden Markov models an selected applications in speech recognition. In Proceedings of the IEEE, 77(2), pp. 257-286.
  20. Schmid, H., 1994. Part-of-speech tagging with neural networks. In Proceedings of the 15th Conference on Computational Linguistics, 1, pp. 172-176.
  21. Soares, C. M., da Silva, C. L. F., De Gregorio, M., França, F. M. G., 1998. Uma implementação em software do classificador WiSARD. In Proceedings of the V Simpósio Brasileiro de Redes Neurais (SBRN 1998), 2, pp. 225-229. (In Portuguese).
  22. Villavicencio, A., Marques, N. M., Lopes, J. G. P., Villavicencio, F., 1995. Part-of-speech tagging for portuguese texts. In Proceedings of the 12th Symposium on Artificial Intelligence, 991, pp. 323- 332.
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Paper Citation


in Harvard Style

Carneiro H., França F. and Lima P. (2010). WANN-TAGGER - A Weightless Artificial Neural Network Tagger for the Portuguese Language . In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 330-335. DOI: 10.5220/0003082303300335


in Bibtex Style

@conference{icnc10,
author={Hugo C. C. Carneiro and Felipe M. G. França and Priscila M. V. Lima},
title={WANN-TAGGER - A Weightless Artificial Neural Network Tagger for the Portuguese Language},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)},
year={2010},
pages={330-335},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003082303300335},
isbn={978-989-8425-32-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)
TI - WANN-TAGGER - A Weightless Artificial Neural Network Tagger for the Portuguese Language
SN - 978-989-8425-32-4
AU - Carneiro H.
AU - França F.
AU - Lima P.
PY - 2010
SP - 330
EP - 335
DO - 10.5220/0003082303300335