• 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