Parsing the Arabic language is a difficult task given the specificities of this language and given the scarcity of digital resources (grammars and annotated corpora). In this paper, we suggest a method for Arabic parsing based on supervised machine learning. We used the SVMs algorithm to select the syntactic labels of the sentence. Furthermore, we evaluated our parser following the cross validation method by using the Penn Arabic Treebank. The obtained results are very encouraging.
@article{arxiv.1410.8783,
title = {Supervised learning model for parsing Arabic language},
author = {Nabil Khoufi and Chafik Aloulou and Lamia Hadrich Belguith},
journal= {arXiv preprint arXiv:1410.8783},
year = {2014}
}
Comments
8 pages,1 figure, Proceedings of the 10th International Workshop on Natural Language Processing and Cognitive Science (NLPCS 2013),2013, Marseille, France, pp129-136