Text Feature Selection Method in Battlefield Information Service

Abstract

The high dimensionality of the current battlefield information increases the complexity of the information utilization, which leads to the deterioration of the battlefield information services. The effective reduction of the of battlefield information dimension by information feature selection is an important prerequisite for the effective development of battlefield information service. The traditional feature selection method is not applicable due to the absence of accurate labels of items in battlefield text information. An attribute reduction method based on set division is proposed and applied to the battlefield text feature selection. An improved document frequency (DF) method for text feature selection is used to filter noise words, then the text feature is selected by the attribute reduction based on set division. Experimental results demonstrate that the proposed feature selection algorithm is able to obtain a better feature subset of battlefield text information when compared with other existing feature selection algorithms.