Similarity and relevance of court decisions: A computational study on CJEU cases

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Identification of relevant or similar court decisions is a core activity in legal
decision making for case law researchers and practitioners. With an ever increasing body of case law, a manual analysis of court decisions can become practically impossible. As a result, some decisions are inevitably overlooked. Alternatively, network analysis may be applied to detect relevant precedents and landmark cases. Previous research suggests that citation networks of court decisions frequently provide relevant precedents and landmark cases. The advent of text similarity measures (both syntactic and semantic) has meant that
potentially relevant cases can be identified without the need to manually read them. However, how close do these measures come to approximating the notion of relevance captured in the citation network? In this contribution, we explore this question by measuring the level of agreement of state-of-the-art text similarity algorithms with the citation behavior in the case citation network. For this paper, we focus on judgements by the Court of Justice of the European Union (CJEU) as published in the EUR-Lex database. Our results show that similarity of the full texts of CJEU court decisions does not closely mirror citation behaviour, there is a substantial overlap. In particular, we found syntactic measures surprisingly outperform semantic ones in approximating the citation network.
Original languageEnglish
Title of host publicationLegal knowledge and information systems
EditorsMichał Araszkiewicz, Víctor Rodríguez-Doncel
Place of PublicationAmsterdam/Berlin/Washington, DC
PublisherIOS Press
Number of pages10
ISBN (Electronic)978-16-4368-049-1
ISBN (Print)978-16-4368-048-4
Publication statusPublished - Dec 2019

Publication series

SeriesFrontiers in Artificial Intelligence and Applications


  • CJEU
  • case law
  • computational
  • similarity
  • Text Similarity
  • LAW
  • Network Analysis
  • Word Embeddings


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