Categorization Arabic Text Using SVM and KNN Algorithms

  • Authors

    • Geehan Sabah Hassan
    • . .
    https://doi.org/10.14419/ijet.v7i3.20.28415
  • text classification (TC), Support Vector Machine (SVM), K–Nearest Neighbor (KNN).

  • Abstract

    Content arrangement is a strategy for marking regular dialect writings with one or a few classifications from a predefined set. Two calculations, to be specific, bolster vector machine (SVM) and k-closest neighbor (KNN), are utilized to examine Arabic content order (TC). Distinctive Arabic datasets are utilized to analyze the two calculations. This examination has been intended to order extraordinary Arabic content. Result demonstrates that TC by means of the SVM calculation beats TC by means of KNN regarding all measures.

     

     

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  • How to Cite

    Sabah Hassan, G., & ., . (2018). Categorization Arabic Text Using SVM and KNN Algorithms. International Journal of Engineering & Technology, 7(3.20), 906-909. https://doi.org/10.14419/ijet.v7i3.20.28415

    Received date: 2019-03-15

    Accepted date: 2019-03-15