Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (8): 80-85.doi: 10.11896/jsjkx.210300130

Special Issue: Natural Language Processing

• Database & Big Data & Data Science • Previous Articles     Next Articles

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

WANG Li-mei1, ZHU Xu-guang2,3, WANG De-jia3, ZHANG Yong4 , XING Chun-xiao4   

  1. 1 School of Criminal Justice,China University of Political Science and Law,Beijing 100088,China;
    2 Institute of Cyber Law,China University of Political Science and Law,Beijing 100088,China;
    3 Jiangsu PayEgis Technology Co.,Ltd.,Suzhou,Jiangsu 215000,China;
    4 Beijing National Research Center for Information Science and Technology,Tsinghua University,Beijing 100084,China
  • Received:2021-03-12 Revised:2021-05-21 Published:2021-08-10
  • About author:WANG Li-mei,born in 1974,Ph.D,professor.Her main research interests include cyber law and so on.(limeiw@cupl.edu.cn)ZHU Xu-guang,born in 1989,master.His main research interests include artificial intelligence and cyber law.
  • Supported by:
    National Key R&D Program(2018YFC0831202).

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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%.

Key words: Big data, Classification, Deep learning, Judgment documents, Judicial data, Natural language processing

CLC Number: 

  • TP391.4
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