|
--- |
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dataset_info: |
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features: |
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- name: text |
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dtype: string |
|
- name: label |
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dtype: string |
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splits: |
|
- name: train |
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num_bytes: 181482477 |
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num_examples: 45500 |
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download_size: 86389093 |
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dataset_size: 181482477 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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task_categories: |
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- text-classification |
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- translation |
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- summarization |
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language: |
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- ar |
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- en |
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size_categories: |
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- 10K<n<100K |
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--- |
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|
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# Arabic News Articles Dataset |
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## About Dataset |
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Context |
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SANAD Dataset is a large collection of Arabic news articles that can be used in different Arabic NLP tasks such as Text Classification and Word Embedding. The articles were collected using Python scripts written specifically for three popular news websites: AlKhaleej, AlArabiya and Akhbarona. |
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All datasets have seven categories [Culture, Finance, Medical, Politics, Religion, Sports and Tech], except AlArabiya which doesn’t have [Religion]. SANAD contains a total number of 190k+ articles. |
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## Content |
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a subset Khaleej (45500 articles in 7 categories) of SANAD. Labels are categorized in: Culture, Finance, Medical, Politics,Religion,Sports,Tech. |
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|
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## Acknowledgements |
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We wouldn't be here without the help of Omar Einea, Ashraf Elnagar, Ridhwan Al-Debsi. |
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https://doi.org/10.1016/j.dib.2019.104076 |
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|
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## Contact |
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**Mouwiya S. A. Al-Qaisieh** |
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[email protected] |
