An efficient rank based Arabic root extractor
Mahmoud Eldefrawy, Nahla A. Belal, Yasser El-Sonbaty · 2017 Intelligent Systems Conference (IntelliSys) · 2017
A morphologically-rich language such as Arabic requires deep analysis; this is due to its invaluable characteristics which are beneficial for the task of root extraction. This paper investigates employing new techniques to enumerate and rank possible roots for a given word, using linguistic rules as scoring mechanisms. The proposed technique extends the use of roots' dictionary to extract new features in order to develop a more accurate root extractor. The proposed root extractor showed an accuracy of 83.9% with at least 11.8% accuracy difference over other root extractors using a direct evaluation dataset.