The aim of this paper is to present the first Amazighe POS tagger. Very few linguistic resources have been developed so far for Amazighe and we believe that the development of a POS tagger tool is the first step needed for automatic text processing. The used data have been manually collected and annotated. We have used state-of-art supervised machine learning approaches to build our POS-tagging models. The obtained accuracy achieved 92.58% and we have used the 10-fold technique to further validate our results. © 2011 Springer-Verlag.
CITATION STYLE
Outahajala, M., Benajiba, Y., Rosso, P., & Zenkouar, L. (2011). POS tagging in Amazighe using support vector machines and conditional random fields. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6716 LNCS, pp. 238–241). https://doi.org/10.1007/978-3-642-22327-3_28
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