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README.md
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The Abu El-Khair Arabic News Corpus (arabic-billion-words) is a comprehensive collection of Arabic text, encompassing over five million newspaper articles. The corpus is rich in linguistic diversity, containing more than a billion and a half words, with approximately three million unique words. The text is encoded in two formats: UTF-8 and Windows CP-1256, and marked up using two markup languages: SGML and XML.
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- Arabic
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### Data Instances
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An example from the "Almasryalyoum" configuration subset:
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```
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The dataset comprises the following fields:
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- "url": string, original URL of the article.
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- "date": string, date of the article.
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- "text": string, textual content of the article.
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The dataset is divided into a single "training" split, with the following distribution of examples across different configuration subsets:
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| Techreen | 314,597 |
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| Youm7 | 1,172,136 |
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This dataset is valuable for natural language processing (NLP) tasks, including but not limited to sentiment analysis, topic modeling, and language modeling in the context of Arabic news articles. Researchers and practitioners in the field of NLP can benefit from the diverse linguistic content and the substantial size of the corpus.
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# Arabic Billion Words Description
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The Abu El-Khair Arabic News Corpus (arabic-billion-words) is a comprehensive collection of Arabic text, encompassing over five million newspaper articles. The corpus is rich in linguistic diversity, containing more than a billion and a half words, with approximately three million unique words. The text is encoded in two formats: UTF-8 and Windows CP-1256, and marked up using two markup languages: SGML and XML.
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## Data Example
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An example from the "Almasryalyoum" configuration subset:
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}
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```
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## Data Fields
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The dataset comprises the following fields:
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- "url": string, original URL of the article.
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- "date": string, date of the article.
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- "text": string, textual content of the article.
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## Data Splits
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The dataset is divided into a single "training" split, with the following distribution of examples across different configuration subsets:
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| Techreen | 314,597 |
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| Youm7 | 1,172,136 |
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## Dataset Usage
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This dataset is valuable for natural language processing (NLP) tasks, including but not limited to sentiment analysis, topic modeling, and language modeling in the context of Arabic news articles. Researchers and practitioners in the field of NLP can benefit from the diverse linguistic content and the substantial size of the corpus.
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