Principal component analysis neural network for textual document categorization and dimension reduction

This manuscript presents the study and application of the method of principal component analysis (PCA) in the field of text mining. We began by studying the theoretical basis behind this method and we have focused on two of its variants namely the neural PCA and kernel PCA. We used neural PCA for automatic categorization of text documents through an extraction of semantic concepts. The second contribution of our work is the use of PCA (neuronal and kernel) for the dimension reduction of textual documents through the automatic classification.