Chinese Text Classification System on Regulatory Information Based on SVM

Abstract

The rapid development of computer technology has brought a large amount of text information. This paper aims to classify the text in view of the increasing number of Chinese texts in the process of supervision and the increasing demand of processing Chinese texts, and to improve the efficiency of information query and management. In this paper, a Chinese text brake classification system based on support vector machine is designed and implemented. The text is represented mathematically by vector space model, and the classifier is trained to classify the text based on the principle of support vector machine. In this paper, the classification performance of the text system is tested and evaluated by using the file of regulatory information. The experimental results show that the classification accuracy of the text system is relatively high and has certain practicability. The system in this paper can improve the efficiency of information inquiry and management and make it possible to manage massive text information.