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.
|Journal||Global Science and Technology Forum Journal of Computing|
|Publication status||Published - 30 Aug 2016|
Mohammad, A. H., Alwada'n, T., & Almomani, O. (2016). Arabic Text Categorization Using Support vector machine, Nave Bayes and Neural Network. Global Science and Technology Forum Journal of Computing, 5(1), 108-115. https://doi.org/10.7603/s40601-016-0016-9