Papers by Ali L. Hatab
Enhancing Deep Learning with Embedded Features for Arabic Named Entity Recognition (2022.lrec-1)
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| Challenge: | Word embeddings can capture the semantics of words and other hidden features, but the Arabic language is complex and requires a large amount of information to process. |
| Approach: | They propose to add morphological and syntactical features to Arabic word embeddings to train the model. |
| Outcome: | The proposed model outperforms the previous systems to the best of our knowledge. |