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Methodical Evaluation of Arabic Word Embeddings

2017-07-01 · ACL 2017 7 · Mohammed Elrazzaz, Shady Elbassuoni, Khaled Shaban, Chadi Helwe

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.

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Document ClassificationLearning Word EmbeddingsNamed Entity Recognition (NER)Word Embeddings

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