Legal case retrieval is a special Information Retrieval~(IR) task focusing on legal case documents. Depending on the downstream tasks of the retrieved case documents, users' information needs in legal case retrieval could be significantly different from those in Web search and traditional ad-hoc retrieval tasks. While there are several studies that retrieve legal cases based on text similarity, the underlying search intents of legal retrieval users, as shown in this paper, are more complicated than that yet mostly unexplored. To this end, we present a novel hierarchical intent taxonomy of legal case retrieval. It consists of five intent types categorized by three criteria, i.e., search for Particular Case(s), Characterization, Penalty, Procedure, and Interest. The taxonomy was constructed transparently and evaluated extensively through interviews, editorial user studies, and query log analysis. Through a laboratory user study, we reveal significant differences in user behavior and satisfaction under different search intents in legal case retrieval. Furthermore, we apply the proposed taxonomy to various downstream legal retrieval tasks, e.g., result ranking and satisfaction prediction, and demonstrate its effectiveness. Our work provides important insights into the understanding of user intents in legal case retrieval and potentially leads to better retrieval techniques in the legal domain, such as intent-aware ranking strategies and evaluation methodologies.

翻译：法律案例检索是一项特殊的 信息检索任务，专注于法律案例文档。根据检索所得案例文档的下游任务，用户在法律案例检索中的信息需求可能与网络搜索和传统临时检索任务存在显著差异。尽管已有研究基于文本相似度检索法律案例，但本文表明，法律检索用户的潜在搜索意图比这更为复杂且大多尚未被探索。为此，我们提出了一种新颖的分层法律案例检索意图分类法。该分类法包含五种意图类型，根据三个标准分类：寻找特定案例、特征化、量刑、程序与利益。分类法通过访谈、编辑用户研究和查询日志分析透明构建并广泛评估。通过实验室用户研究，我们揭示了法律案例检索中不同搜索意图下用户行为与满意度的显著差异。此外，我们将所提议的分类法应用于各种下游法律检索任务（如结果排序与满意度预测），并证明了其有效性。我们的工作为理解法律案例检索中的用户意图提供了重要见解，并有望推动法律领域检索技术的改进，例如意图感知的排序策略与评估方法论。