Abstract
In this paper, we address the problem of Part-Of-Speech tagging of Arabic texts with vowel marks. After the description of the specificities of Arabic language and the induced difficulties on the task of POS-tagging, we propose an approach combining several methods. One of these methods, based on sentences patterns, is original and very attractive. We present, afterward, the multi-agent architecture that we adopted for the conception and the realization of our POS-tagging system. The multi-agent architecture is justified by the need for collaboration, parallelism and competition between the different agents. Finally, we expose the implementation and the evaluation of the system implemented.
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References
Cutting, D., Kupiec, J., Pedersen, J., And Sibun, P.: A practical Part-Of-Speech Tagger. In: Proceedings of the Third Conference on Applied Natural Language Processing, pp. 133–140 (1992)
Schmid, H., Stein, A., et al.: Etiquetage morphologique de textes français avec un arbre de décision. Le traitement automatique des langues: Traitements probabilistes et corpus 36(1-2), 23–35 (1995)
Adwait, R.: A maximum Entropy Model for part of speech tagger. In: Proceedings of the first empirical methods in natural language processing conference, Philadelphia, USA, pp. 133–142 (1996)
Brill, E.: Some Advances in Transformation-based part of speech Tagging. In: Proceedings of the 12th national conference on artificial intelligence, pp. 722–727 (1992)
Marshall, I.: Choice of Grammatical Word-class without Global Syntactic Analysis: Tagging Words in the LOB Corpus. Computers and the Humanities 17, 139–150 (1983)
Brill, E., Wu, J.: Classifier combination for improved lexical disambiguation. In: Proceedings of the thirty-sixth ACL and seventeenth COLING, Montréal, Canada, pp. 191–195 (1998)
Jonas, S.: Combining POS-Taggers for improved accuracy on Swedish text, NoDaLiDa, Reykjavik (2003)
Debili, F., Achour, H., Souissi, E.: La langue arabe et l’ordinateur: de l’étiquetage grammatical à la voyellation automatique. Correspondances, vol. 71, Institut de recherche sur le Maghreb contemporain, CNRS, Tunis, pp. 10–28 (2002)
Khoja, S.: APT: Arabic Part-of-speech Tagger. In: Proceedings of the student workshop at the second meeting of the north American chapter of the Association for computational linguistics (NAACL 2001), pp. 20–26. Carnegie Mellon University, Pennsylvania (2001)
Zemirli, Z., Khabet, S., et al.: TAGGAR : un analyseur morphosyntaxique destiné à la synthèse vocale des textes arabes voyellés. JEP-TALN 2004, Traitement Automatique de l’Arabe, Fès (2004)
Ben Othman, C.: De la synthèse lexicographique à la détection et la correction des graphie fautives arabes. Thèse de doctorat, Université de Paris XI, Orsay (1998)
Rajman, M., Chappelier, J.C., et al.: Chaînes de Markov cachées. Cours TIDT, Département informatique, Ecole Polytechnique de la Lausanne (2003)
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© 2006 Springer-Verlag Berlin Heidelberg
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Zribi, C.B.O., Torjmen, A., Ahmed, M.B. (2006). An Efficient Multi-agent System Combining POS-Taggers for Arabic Texts. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2006. Lecture Notes in Computer Science, vol 3878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11671299_15
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DOI: https://doi.org/10.1007/11671299_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32205-4
Online ISBN: 978-3-540-32206-1
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