Study on Judicial Data Classification Method Based on Natural Language Processing Technologies

Abstract

The rapid increase in the number of judgment documents puts forward an urgent need for automated classification.However,there is a lack of method in existing studies that use judgment results as the subject of classification in the subdivision of civil cases,and therefore they cannot achieve accurate classification of judgment results in civil cases.In this paper,we apply deep learning technology in the field of classification of judgment results of civil cases,and obtain a model with better perfor-mance in this field through horizontal comparison of multiple deep learning models.This model is further optimized based on the data characteristics of the judgment document.After experiments,the Transformer model's macro precision rate,macro recall rate and macro F1 score in the judgment result classification are all higher than other models.By adjusting the data preprocessing process and adjusting the position embedding method of the Transformer model,the performance index of the model is increased by 1%～2%.

Keywords

• big data|judicial data|judgment documents|natural language processing|classification|deep learning