Abstract:

In view of the disadvantages of traditional feature selection algorithm, we proposed a new feature selection algorithm, which simultaneously measures the importance of one feature both in intracategory and intercategory. The proposed algorithm was compared with five feature selection algorithms via two classification algorithms on three benchmark document collections. The experimental results show the proposed method can reduce the dimensionality
 of the text representation and significantly improve the performance of the text categorization.

Key words: feature selection, text categorization, dimensionality reduction