Abstract
Part-of-speech tagging is a task of considerable importance in the field of natural language processing. Its purpose is to automatically tag the words of a text with labels that designate the appropriate parts-of-speech. The approach proposed in this paper divides the problem into two tasks: a learning task and an optimization task. Algorithms from the field of evolutionary computation were adopted to tackle each of those tasks. We emphasize the use of swarm intelligence, not only for the good results achieved, but also because it is one of the first applications of such algorithms to this problem. This approach was designed with the aim of being easily extended to other natural language processing tasks that share characteristics with the part-of-speech tagging problem. The results obtained in two different English corpora are among the best published.
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References
Brill, E.: Transformation-based error-driven learning and natural language processing: a case study in part-of-speech tagging. Comput. Linguist. 21, 543–565 (1995)
Wilson, G., Heywood, M.: Use of a genetic algorithm in brill’s transformation-based part-of-speech tagger. In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, GECCO 2005, pp. 2067–2073. ACM, New York (2005)
Nogueira Dos Santos, C., Milidiú, R.L., Rentería, R.P.: Portuguese part-of-speech tagging using entropy guided transformation learning. In: Teixeira, A., de Lima, V.L.S., de Oliveira, L.C., Quaresma, P. (eds.) PROPOR 2008. LNCS (LNAI), vol. 5190, pp. 143–152. Springer, Heidelberg (2008)
Araujo, L.: Part-of-speech tagging with evolutionary algorithms. In: Gelbukh, A. (ed.) CICLing 2002. LNCS, vol. 2276, pp. 230–239. Springer, Heidelberg (2002)
Alba, E., Luque, G., Araujo, L.: Natural language tagging with genetic algorithms. Inf. Process. Lett. 100(5), 173–182 (2006)
Sousa, T., Neves, A., Silva, A.: Swarm optimisation as a new tool for data mining. In: Proceedings of the 17th International Symposium on Parallel and Distributed Processing, IPDPS 2003, p. 144. IEEE Computer Society, Washington, DC (2003)
Sousa, T., Silva, A., Neves, A.: Particle swarm based data mining algorithms for classification tasks. Parallel Computing 30(5), 767–783 (2004)
Silva, A.P., Silva, A., Rodrigues, I.: Biopos: Biologically inspired algorithms for pos tagging. In: Proceedings of the 1st International Workshop on Optimization Techniques for Human Language Technology, OPTHLT/COLING 2012, Mumbai, India, pp. 1–16 (December 2012)
Silva, A.P., Silva, A., Rodrigues, I.: Tagging with disambiguation rules: A new evolutionary approach to the part-of-speech problem. In: Proceedings of the 4th International Conference on Evolutionary Computation Theory and Applications, IJCCI 2012, Barcelona, pp. 5–14 (2012)
Steven Bird, E.K., Loper, E.: Natural Language Processing with Python. O’Reilly Media (2009)
Kennedy, J., Eberhart, R.C.: Swarm intelligence. Morgan Kaufmann Publishers Inc., San Francisco (2001)
Holland, J.: Genetic Algorithms. Scientific American 267(1) (July 1992)
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Silva, A.P., Silva, A., Rodrigues, I. (2014). Part-of-Speech Tagging Using Evolutionary Computation. In: Terrazas, G., Otero, F., Masegosa, A. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2013). Studies in Computational Intelligence, vol 512. Springer, Cham. https://doi.org/10.1007/978-3-319-01692-4_13
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DOI: https://doi.org/10.1007/978-3-319-01692-4_13
Publisher Name: Springer, Cham
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