Arabic Text Categorization using Machine Learning Approaches

Arabic Text categorization is considered one of the severe problems in classification using machine learning algorithms. Achieving high accuracy in Arabic text categorization depends on the preprocessing techniques used to prepare the data set. Thus, in this paper, an investigation of the impact of the preprocessing methods concerning the performance of three machine learning algorithms, namely, Na¨ıve Bayesian, DMNBtext and C4.5 is conducted. Results show that the DMNBtext learning algorithm achieved higher performance compared to other machine learning algorithms in categorizing Arabic text.

@article{Alshammari2018,
  title     = {Arabic Text Categorization using Machine Learning Approaches},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {3},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Riyad Alshammari},
  doi       = {10.14569/IJACSA.2018.090332},
  url       = {https://doi.org/10.14569/IJACSA.2018.090332}
}