A Possibilistic Approach for Arabic Domain Terminology Extraction and Translation

This paper proposes a hybrid possibilistic approach for bilingual terminology extraction using possibility and necessity measures. On the one hand, we extract domain-relevant terms from the source language, and on the other hand, we build a co-occurrence-based translation graph, which is mined to translate terms in the target language. We compare our approach with different state-of-the art approaches. Experimental results show that the possibilistic approach reaches better results in terms of Recall, Precision and Mean Average Precision (MAP). The differences between the compared approaches show that our contribution is significant in terms of p-value.