Abstract
This paper aims to present an alternative view on the task of morphological tagging - a rule based system with new and simple learning method that uses just basic arithmetic operations to create an efficient knowledge base. Matching process of this rule-based approach follows specific-to-general technique, where rules for more specific contexts are applied whenever they are available in the rule-base. As a consequence, the major accuracy and performance improvements can be achieved by pruning the rule-base.
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Nouza, J., Zdansky, J., Cerva, P., Silovsky, J.: Challenges in Speech Processing of Slavic Languages (Case Studies in Speech Recognition of Czech and Slovak). In: Esposito, A., Campbell, N., Vogel, C., Hussain, A., Nijholt, A. (eds.) COST 2102 Int. Training School 2009. LNCS, vol. 5967, pp. 225–241. Springer, Heidelberg (2010)
Beňuš, S., Cerňak, M., Rusko, M., Trnka, M., Darjaa, S.: Adapting slovak asr for native germans speaking slovak. In: Proceedings of the First Workshop on Algorithms and Resources for Modelling of Dialects and Language Varieties, DIALECTS 2011, pp. 60–64. Association for Computational Linguistics, Stroudsburg (2011)
Brants, T.: Tnt: A statistical part-of-speech tagger. In: Proc. of the Sixth Conference on Applied Natural Language Processing, ANLC 2000, pp. 224–231. Association for Computational Linguistics, Stroudsburg (2000)
Collins, M.: Discriminative training methods for hidden markov models: Theory and experiments with perceptron algorithms. In: Proceedings of the ACL 2002 Conference on Empirical Methods in Natural Language Processing, vol. 10, pp. 1–8. Association for Computational Linguistics (2002)
Schmid, H., Laws, F.: Estimation of conditional probabilities with decision trees and an application to fine-grained POS tagging. In: Proceedings of the 22nd International Conference on Computational Linguistics, vol. 1, pp. 777–784. Association for Computational Linguistics (2008)
Toutanova, K., Klein, D., Manning, C.D., Singer, Y.: Feature-rich part-of-speech tagging with a cyclic dependency network. In: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, NAACL 2003, vol. 1, pp. 173–180. Association for Computational Linguistics, Stroudsburg (2003)
Spoustová, D., Hajič, J., Raab, J., Spousta, M.: Semi-supervised training for the averaged perceptron pos tagger. In: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2009, pp. 763–771. Association for Computational Linguistics, Stroudsburg (2009)
Spoustová, D., Hajič, J., Votrubec, J., Krbec, P., Květoň, P.: The best of two worlds: Cooperation of statistical and rule-based taggers for Czech. In: Proc. of the Workshop on Balto-Slavonic Natural Language Processing: Information Extraction and Enabling Technologies, pp. 67–74. Association for Computational Linguistics (2007)
Holland, J.H.: Escaping brittleness: the possibilities of general-purpose learning algorithms applied to parallel rule-based systems. Machine Learning: An Artificial Intelligence Approach 2 (1986)
Sigaud, O., Wilson, S.: Learning classifier systems: a survey. Soft Computing-A Fusion of Foundations, Methodologies and Applications 11(11), 1065–1078 (2007)
Hládek, D.: Learning System Based on Generalization of Fuzzy Rules. PhD thesis, Technical University of Kosice (2009)
Jazykovedný ústav Ľ. Štúra SAV: Slovenský národný korpus prim-3.0-public-all (2007)
Horák, A., Gianitsová, L., Šimková, M., Šmotlák, M., Garabík, R.: Slovak National Corpus. In: Sojka, P., Kopeček, I., Pala, K., et al. (eds.) TSD 2004. LNCS (LNAI), vol. 3206, pp. 89–93. Springer, Heidelberg (2004)
Halácsy, P., Kornai, A., Oravecz, C.: HunPos - An open source trigram tagger. In: Proc. of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions, ACL 2007, pp. 209–212. Association for Computational Linguistics, Stroudsburg (2007)
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Hládek, D., Staš, J., Juhár, J. (2012). Rule-Based Morphological Tagger for an Inflectional Language. In: Esposito, A., Esposito, A.M., Vinciarelli, A., Hoffmann, R., Müller, V.C. (eds) Cognitive Behavioural Systems. Lecture Notes in Computer Science, vol 7403. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34584-5_17
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DOI: https://doi.org/10.1007/978-3-642-34584-5_17
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