A new feature selection method for text categorization

How to reduce feature dimension while maintaining categorization accuracy is a key issue of text categorization.A new method based on information theory was proposed to solve this problem.This approach aims to eliminate sparsely distributed features and find features useful for categorization.Working with these feature reduction methods,it could further reduce the feature dimension.The performance of this proposed method was tested on benchmark text classification problems.The results showed that it could not only reduce the feature dimension to hundreds but also improve the performance.