JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2021, Vol. 56 ›› Issue (11): 24-30.doi: 10.6040/j.issn.1671-9352.1.2020.043

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Method of recommendation based on knowledge driven by BERT and law

TANG Guang-yuan1,2 , GUO Jun-jun1,2 , YU Zheng-tao1,2, ZHANG Ya-fei 1,2,GAO Sheng-xiang1,2   

  1. 1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, Yunan, China;
    2. Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming 650500, Yunnan, China
  • Published:2021-11-15

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Abstract: Aiming at the problem of insufficient knowledge utilization of traditional law recommendation methods, this article combines the pre-training BERT(bidirectional encoder representation from transformers)model to propose a law recommendation method based on knowledge-driven legal provisions in the judicial field. First based on the BERT pre-training model, the legal knowledge and the case description are characterized separately, and the case description text is extracted based on the two-way LSTM, and then the case description text features combined with the legal knowledge are extracted based on the attention mechanism, and the intelligent recommendation of the legal clause is finally realized. Using this method on the law research cup public data set, the recommended F1 value of the law can reach 0.88. From this effect, it can be seen that the BERT model fused with knowledge of the law can significantly improve the law recommendation and can effectively solve the easily confused method of recommended questions.

Key words: recommendation of law, BERT model, knowledge fusion of law, attention mechanism

CLC Number: 

  • TP391
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