Work

Supervised learning model for parsing Arabic language

Year: 2014

Type: preprint

Abstract: 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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1410.8783

Authors: Khoufi, Nabil, Aloulou, Chafik, Belguith, Lamia Hadrich

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W204419384

Cites: 7

Cited by: 5

Related to: 10