Diverse legal case search

TL;DR

This paper introduces a novel legal case retrieval model that emphasizes diversity and relevance, addressing the interconnected nature of legal causes of action, and provides a new dataset with manual labels to evaluate its effectiveness.

Contribution

The paper proposes a specialized diversity legal retrieval model and creates a new labeled dataset, tailored to the unique interconnected scenarios of legal case search.

Findings

The model effectively balances diversity and relevance in legal search results.

Experiments show improved retrieval performance over existing methods.

The dataset with manual labels supports future research in legal information retrieval.

Abstract

In last decades, legal case search has received more and more attention. Legal practitioners need to work or enhance their efficiency by means of class case search. In the process of searching, legal practitioners often need the search results under several different causes of cases as reference. However, existing work tends to focus on the relevance of the judgments themselves, without considering the connection between the causes of action. Several well-established diversity search techniques already exist in open-field search efforts. However, these techniques do not take into account the specificity of legal search scenarios, e.g., the subtopic may not be independent of each other, but somehow connected. Therefore, we construct a diversity legal retrieval model. This model takes into account both diversity and relevance, and is well adapted to this scenario. At the same time, considering the lack of dataset with diversity labels, we constructed a diversity legal retrieval dataset and obtained labels by manual labeling. experiments confirmed that our model is effective.