Towards Legal Case Retrieval

Legal case retrieval is a specialized IR task that aims to retrieve supporting precedents given a query case. Different from the traditional ad-hoc text retrieval, the query case is much longer and complex than common keyword queries. Legal relevance between a supporting case and a query case is defined beyond general topical relevance and it requires legal knowledge to make relevance judgment. It is thus difficult to collect a large-scale case retrieval dataset along with accurate relevance judgments. Therefore, legal case retrieval is more challenging. As a primary attempt, we propose to develop a retrieval model to tackle these challenges based on the benchmarks in this task. Moreover, we plan to investigate the practical interactions between legal practitioners and retrieval systems and further apply the user behavior models to improve system performance. Beyond the binary labels, we would like to take a deeper look at the decision process of relevance judgment in legal practice, which will benefit related tasks such as relevance estimation and result ranking.