Computer Science

Computer Science ›› 2026, Vol. 53 ›› Issue (7): 118-124.doi: 10.11896/jsjkx.250600009

• Artificial Intelligence • Previous Articles     Next Articles

From Boolean Retrieval to Foundational Models:Legal Perspective on Development of Case Retrieval Technology

SHI Yiran1, ZHANG Linghan2, LIU Yiqun3   

  1. 1 The Institute for Data Law,China University of Political Science and Law,Beijing 100088,China
    2 The Institute of AI Law and Governance,China University of Political Science and Law,Beijing 100088,China
    3 Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China
  • Received:2025-06-03 Revised:2025-11-21 Online:2026-07-15 Published:2026-07-10
  • About author:SHI Yiran,born in 1999,Ph.D canidate.Her main research interests include data law and AI law.
    ZHANG Linghan,born in 1982,Ph.D,professor,Ph.D supervisor.Her main research interests include AI(algorithms),data,and platform governance.
  • Supported by:
    2024 Ministry of Justice Key Research Project on Construction of Rule of Law and Legal Theory(24SFB1011) and 2025 China University of Political Science and Law Research Innovation Project(10825383).

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Abstract: Technological innovation,exemplified by artificial intelligence,is reshaping judicial practice and driving the development of “smart courts”.In this context,similar case retrieval technology,as a key application of AI,is evolving from traditional keyword-based searches and shallow text matching to intelligent retrieval based on deep semantic understanding,contextual awareness,and logical reasoning.AI-powered retrieval can partially simulate judges' reasoning processes,improving efficiency,promoting consistency in legal application,and enhancing judicial fairness.However,in-depth interviews with frontline judges reveal a significant gap between the technology used in practice and the advancements seen in research.This gap manifests in three main respects:1)Etrieval methods remain predominantly keyword-based,with semantic-level retrieval yet to be widely adopted,resulting in limited efficiency.2)Retrieval quality remains inadequate,as existing databases struggle to balance case volume with case authority,and a unified and explicit standard for defining “similar cases” is still lacking.3)Retrieval rules are incomplete,with insufficient differentiation based on jurisdiction,trial level,and the legal effect of judgments.Drawing on the application of mainstream retrieval platforms,this paper adopts a mixed method combining cross-platform comparison with longitudinal technical analysis.From both legal theory and judicial practice perspectives,it examines the current development and existing bottlenecks of similar case retrieval technology and proposes directions for future improvement.

Key words: Legal case retrieval, Pre-trained model, Law, Artificial Intelligence(AI), Smart courts

CLC Number: 

  • TP181
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