Comparative study of word embedding models for Arabic terminology extraction

TitleComparative study of word embedding models for Arabic terminology extraction
Publication TypeConference Paper
Year of Publication2018
AuthorsLahbib, W, Bounhas, I, Slimani, Y
Conference NameApplied Computing conference, pp. 245-252
Date Published10/2018
Conference LocationBudapest, Hungary
Other Numbers231-238
KeywordsArabic bilingual terminology, Graph-mining, Possibility theory

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.


Arabic TALN & IR



This paper proposes a corpus

This paper proposes a corpus-based possibilistic approach for BTE. We opt for a corpus-based approach as bilingual dictionaries are hard to build and are not available for all domains.


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