In case law, the precedents are the relevant cases that are used to support the decisions made by the judges and the opinions of lawyers towards a given case. This relevance is referred to as the case-to-case reference relation. To efficiently find relevant cases from a large case pool, retrieval tools are widely used by legal practitioners. Existing legal case retrieval models mainly work by comparing the text representations of individual cases. Although they obtain a decent retrieval accuracy, the intrinsic case connectivity relationships among cases have not been well exploited for case encoding, therefore limiting the further improvement of retrieval performance. In a case pool, there are three types of case connectivity relationships: the case reference relationship, the case semantic relationship, and the case legal charge relationship. Due to the inductive manner in the task of legal case retrieval, using case reference as input is not applicable for testing. Thus, in this paper, a CaseLink model based on inductive graph learning is proposed to utilise the intrinsic case connectivity for legal case retrieval, a novel Global Case Graph is incorporated to represent both the case semantic relationship and the case legal charge relationship. A novel contrastive objective with a regularisation on the degree of case nodes is proposed to leverage the information carried by the case reference relationship to optimise the model. Extensive experiments have been conducted on two benchmark datasets, which demonstrate the state-of-the-art performance of CaseLink. The code has been released on https://github.com/yanran-tang/CaseLink.

中文翻译：

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CaseLink：用于法律案例检索的归纳图学习

在判例法中，先例是用于支持法官对特定案件做出的决定和律师意见的相关案例。这种相关性被称为个案参考关系。为了从庞大的案例库中高效地查找相关案例，检索工具被法律从业者广泛使用。现有的法律案例检索模型主要通过比较个案的文本表示来工作。尽管它们获得了不错的检索精度，但案例之间内在的案例连接关系尚未得到很好的利用来进行案例编码，因此限制了检索性能的进一步提高。案件池中存在三种案件关联关系：案件引用关系、案件语义关系、案件法律指控关系。由于法律案例检索任务中的归纳方式，使用案例参考作为输入不适用于测试。因此，本文提出了一种基于归纳图学习的 CaseLink 模型，利用案件内在的连通性进行法律案件检索，并采用新颖的全局案件图来表示案件语义关系和案件法律指控关系。提出了一种新颖的对案例节点度进行正则化的对比目标，以利用案例参考关系携带的信息来优化模型。我们在两个基准数据集上进行了广泛的实验，证明了 CaseLink 的最先进的性能。代码已发布于https://github.com/yanran-tang/CaseLink。