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Application of Image Segmentation Algorithm Based on Partial Differential Equation in Legal Case Text Classification
Author(s) -
Jingliang Sun
Publication year - 2021
Publication title -
advances in mathematical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.283
H-Index - 23
eISSN - 1687-9139
pISSN - 1687-9120
DOI - 10.1155/2021/4062200
Subject(s) - computer science , image segmentation , segmentation , function (biology) , algorithm , pattern recognition (psychology) , image (mathematics) , artificial intelligence , text segmentation , data mining , evolutionary biology , biology
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.

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