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Titlebook: Computational Linguistics and Intelligent Text Processing; 12th International C Alexander F. Gelbukh Conference proceedings 2011 Springer B

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An Efficient Part-of-Speech Tagger for Arabicer achieves an accuracy of 95.57% on a standard tagset for Arabic. A detailed error analysis is provided for a better evaluation of the system. We also applied the same approach on different languages like Farsi and German to show the language independent aspect of the approach. Accuracy rates on these languages are also provided.
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The World Youth Festival in Prague, 1947,ser on the projected trees. In this paper, we introduce a simple algorithm using a combination of various word-alignment symmetrizations. We prove that our method outperforms previous work, even though it uses McDonald’s maximum-spanning-tree parser as it is, without any “unsupervised” modifications.
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https://doi.org/10.1007/978-3-319-58241-2lowing systematic control of interaction between rules. Experimental results of our approach on English show that we achieve in the best accuracy published to date: 97.095% on the Penn Treebank corpus. We also obtain the best performance for Vietnamese VietTreeBank corpus.
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On Going Out and the Experience of Studentsd as appropiate because they are designed to treat native language. This paper analyzes the reliability of two part-of-speech taggers on second language Spanish and investigates the most frequent tagger errors and the impact of learner errors in the performance of the taggers.
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