Abstract: Many unsupervised learning techniques have been proposed to obtain meaningful representations of words from text. In this study, we evaluate these various techniques when used to generate Arabic word embeddings. We first build a benchmark for the Arabic language that can be utilized to perform intrinsic evaluation of different word embeddings. We then perform additional extrinsic evaluations of the embeddings based on two NLP tasks. 2017 Association for Computational Linguistics. This work was made possible by NPRP 6-716-1-138 grant from the Qa...
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Topics: 
Natural language processing
Artificial intelligence