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On the Impact of Dataset Characteristics on Arabic Document Classification

This paper describes the impact of dataset characteristics on the results of Arabic document classification algorithms using TF-IDF representations.The experiments compared different stemmers, different categories and different training set sizes, and found that different dataset characteristics produced widely differing results, in one case attaining a remarkable 99% recall (accuracy).The use of a standard dataset would eliminate this variability and enable researchers to gain comparable knowledge from the published results.

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