Research on cross-language text intelligence classification method based on deep learning

Abstract

Text intelligence classification is the basic work in the field of intelligence analysis. At present, text intelligence classification work is usually oriented to a single language, and there are relatively few studies on cross-language text intelligence classification. A text intelligence deep learning classification model based on "XLM-R+TextCNN" is proposed for the problem of cross-language text intelligence classification. The vectorized representation of text information irrelevant to the specific language representation is obtained, and the text vector is input into the TextCNN model to learn the category features of text information, so as to realize the classification of cross-language text information. Based on open-source defense science and technology intelligence, we construct a cross-language text intelligence classification dataset and test the model. Experiments show that the model has achieved good results in several comparative evaluations, proving the feasibility and effectiveness of this method.

Keywords

• text intelligence|classification|cross-language|xlm-r|textcnn