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Arabic Text Classification Using Polynomial Networks
| المصدر: | مجلة جامعة الملك سعود - علوم الحاسب والمعلومات |
|---|---|
| الناشر: | جامعة الملك سعود |
| المؤلف الرئيسي: | Al-Tahrawi, Mayy M. (Author) |
| مؤلفين آخرين: | Al-Khatib, Sumaya N. (Co-Author) |
| المجلد/العدد: | مج27, ع4 |
| محكمة: | نعم |
| الدولة: |
السعودية |
| التاريخ الميلادي: |
2015
|
| الصفحات: | 437 - 449 |
| DOI: |
10.33948/0584-027-004-008 |
| ISSN: |
1319-1578 |
| رقم MD: | 973738 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | science |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Polynomial Networks | Arabic Text Classification | Arabic Document Categorizatio
|
| رابط المحتوى: |
| المستخلص: |
In this paper, an Arabic statistical learning-based text classification system has been developed using Polynomial Neural Networks. Polynomial Networks have been recently applied to English text classification, but they were never used for Arabic text classification. In this research, we investigate the performance of Polynomial Networks in classifying Arabic texts. Experiments are conducted on a widely used Arabic dataset in text classification: Al-Jazeera News dataset. We chose this dataset to enable direct comparisons of the performance of Polynomial Networks classifier versus other well-known classifiers on this dataset in the literature of Arabic text classification. Results of experiments show that Polynomial Networks classifier is a competitive algorithm to the state-of-the-art ones in the field of Arabic text classification. |
|---|---|
| ISSN: |
1319-1578 |
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