Neural Network for Arabic Text Classification

This paper proposes the application of Artificial Neural Network for the classification of Arabic language documents. The automatic classification of Arabic documents using ANN has not been explored in detail so far. In this paper, an Arabic corpus is used to construct and test the ANN model. Methods of document representation, assigning weights that reflect the importance of each term are discussed. Each Arabic document is represented by the term-weighting scheme. As the number of unique words in the collection set is big, the Singular Value Decomposition (SVD) has been used to select the most relevant features for the classification. The experimental results show that ANN model using SVD achieves 88.33% which is better than the performance of basic ANN which yields 85.75% on Arabic document classification.