Neural Network Approaches for Text Document Categorization

This paper presents our research in text document categorization using neural networks. In text document categorization typically the feature spaces have high dimensions, training data are large and the categories are many. A single neural network is often not sufficient to provide accurate classification or efficient training. We present a hierarchical neural network system and a categorical neural network system for document classification. We will show with an application in engineering diagnostic document categorization that the two proposed systems are more effective and efficient than a single neural network, and the hierarchical neural network system gives the highest accuracy in document categorization.