Classification of Arabic Text Using Singular Value Decomposition and Fuzzy C-Means Algorithms

This paper proposes the use of singular value decomposition and fuzzy c-means algorithms for Arabic text classification. Al Jazeera Arabic news and CNN Arabic news datasets are used to measure the effectiveness of the proposed approach in classifying Arabic texts. The experimental results are compared with four supervised classification methods that have been used in the previous work on the same datasets we used in this research. These include: support vector machine, naive Bayes, decision tree, and polynomial networks. The results proved the effectiveness of the proposed approach compared to recent works in Arabic text classification.

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