Arabic Text Categorization Using Support vector machine, Naïve Bayes and Neural Network

Adel Hamdan Mohammad, Tariq Alwada’n, Omar Al-Momani


Text classification is a very important area in
information retrieval. Text classification
techniques used to classify documents into a set
of predefined categories. There are several
techniques and methods used to classify data and
in fact there are many researches talks about
English text classification. Unfortunately, few
researches talks about Arabic text classification.
This paper talks about three well-known
techniques used to classify data. These three
well-known techniques are applied on Arabic
data set. A comparative study is made between
these three techniques. Also this study used fixed
number of documents for all categories of
documents in training and testing phase. The
result shows that the Support Vector machine
gives the best results.


Text Categorization, Naïve Bayesian, Text Classification, Support Vector Machine, Multilayer Perceptron Neural Network

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