时间：2021-10-21
本文Semantic Matching of Legal Cases for large Scale Judgments of China原载2021 16th International Conference on Computer Science & Education (ICCSE)，由四川大学王竹教授等科研人员创作，系四川大学市场经济法治研究所系列学术成果。后续会持续分享四川大学市场经济法治研究所系列学术成果，欢迎大家阅读。
Abstract: With the development of China’s judicial cause and the technological innovation of artificial intelligence, artificial judicial intelligence has become an essential power in judicial trials. Now, more than 100 million judgments have been published online. The combination of existing literature data and natural language processing technology in artificial intelligence is of great value to judge’s trial work. In order to achieve judicial justice, judges need to refer to similar cases in which the previous judgments take effect.At the present stage, the retrieval of similar cases mainly uses keyword retrieval, legal provisions retrieval, and other methods. This kind of method is not accurate enough.From the perspective of semantic matching, this paper analyzes the judgment documents first, points out the important fact that the controversial focus is the high concentration of the facts of the case. Then, we construct a data set in the form of (query: Q, document 1: D1, document 2: D2); On this basis, this paper proposes a multi-task BCKS model. The follow-up experiments show that this method has a good effect and can achieve 91% accuracy when the data size is large enough, which provides strong technical support for the case retrieval system.
Keywords: {Technological innovation; Law; Semantics;Education; Data models; Natural language processing;Complexity theory; case retrieval; case fact; controversial focus; semantic matching}
Y. Mou, Y. Weng, S. Gu and Z. Wang, "Semantic Matching of Legal Cases for large Scale Judgments of China," 2021 16th International Conference on Computer Science & Education (ICCSE), Lancaster, United Kingdom, 2021, pp. 1120-1125.（论文下载）
