Application of Image Segmentation Algorithm Based on Partial Differential Equation in Legal Case Text Classification

Abstract

As a means of regulating people’s code of conduct, law has a close relationship with text, and text data has been growing exponentially. Managing and classifying huge text data have become a huge challenge. The PDES image segmentation algorithm is an effective natural language processing method for text classification management. Based on the study of image segmentation algorithm and legal case text classification theory, an image segmentation model based on partial differential equation is proposed, in which diffusion indirectly acts on level set function through auxiliary function. The software architecture of image segmentation algorithm text classification system is proposed by using computer technology and three-layer architecture model, which can improve the classification ability of text classification algorithm. The validity of pDE image segmentation model is verified by experiments. The experimental results show that the model completes the legal case text classification, the performance of each functional module of the legal case text classification system is good, and the efficiency and quality of the legal case text classification are improved.

Research on case classification algorithm based on BERT-CNN

“…At the same time, many research scholars have creatively put forward many viewpoints based on these baseline models. Sun Jingliang [10] creatively applied the partial differential equation algorithm based on image segmentation to legal case text classification. Yu XS [11] and others proposed an electronic medical record classification method based on text feature dimensionality reduction LSTM.…”