App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 7

Legal judgment prediction using case feature enhancement based on knowledge graph

Li Ziyanga
Zhang Yajuana
Huang Yixionga
Wang Yunhea,b
a. School of Artificial Intelligence, b. Hebei Key Laboratory of Big Data Computing, Hebei University of Technology, Tianjin 300401, China
DOI: 10.19734/j.issn.1001-3695.2023.11.0533

Abstract

The existing legal judgment prediction methods based on knowledge graph focus on the element entities and relationships of the case, and cannot adequately capture the characteristic information of the case. Aiming at this problem, the study proposed a knowledge graph legal judgment prediction method that enhances the fusion of case features. Firstly, this method used bidirectional gated recurrent neural network to mine the deep semantic feature information such as causality and time sequence of fact description text. Then, the feature representation of the learning class case was calculated by the similarity attention between cases in the knowledge graph vector space. Finally, the fusion of feature information and structured knowledge of knowledge graph enriched the semantic feature representation of entities and relationships in the case fact text, and realizes the legal judgment link prediction task. The experimental results on the two types of crime datasets of dangerous driving and theft show that the method improves the two key evaluation indicators of MRR and Hit@1 by about 1.5% compared with the current best-performing link prediction model. The indicators such as Hit@3 and Hit@10 are also improved, which verifies that the case feature enhancement fusion can supplement the missing case feature information in the legal knowledge graph and improve the prediction effect.

Foundation Support

国家青年科学基金项目(62206086)
天津市教委科研计划项目(2022KJ099)
河北省自然科学基金项目(F2023202062)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.11.0533
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 7

Publish History

[2024-01-22] Accepted Paper

Cite This Article

李紫阳, 张亚娟, 黄义雄, 等. 基于知识图谱的案件特征增强法律判决预测 [J]. 计算机应用研究, 2024, 41 (7). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.11.0533. (Li Ziyang, Zhang Yajuan, Huang Yixiong, et al. Legal judgment prediction using case feature enhancement based on knowledge graph [J]. Application Research of Computers, 2024, 41 (7). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.11.0533. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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