Title of article :
Arabic text classification using Polynomial Networks
Author/Authors :
Al-Tahrawi, Mayy M. Al-Ahliyya Amman University - Faculty of Information Technology - Computer Science Department, Jordan , Al-Khatib, Sumaya N. Al-Ahliyya Amman University - Faculty of Information Technology - Software Engineering Department, Jordan
From page :
437
To page :
449
Abstract :
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
Keywords :
Polynomial Networks , Arabic text classification , Arabic document categorization
Journal title :
Journal Of King Saud University - Computer an‎d Information Sciences
Journal title :
Journal Of King Saud University - Computer an‎d Information Sciences
Record number :
2713654
Link To Document :
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