Legal Search in Case Law and Statute Law

Open Access
Authors
Publication date 2019
Host editors
  • M. Araszkiewicz
  • V. Rodríguez-Doncel
Book title Legal Knowledge and Information Systems
Book subtitle JURIX 2019: The Thirty-second Annual Conference
ISBN
  • 9781643680484
ISBN (electronic)
  • 9781643680491
Series Frontiers in Artificial Intelligence and Applications
Event 32nd International Conference on Legal Knowledge and Information Systems (JURIX 2019)
Pages (from-to) 83-92
Publisher Amsterdam: IOS Press
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam Business School Research Institute (ABS-RI)
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract In this work we describe a method to identify document pairwise relevance in the context of a typical legal document collection: limited resources, long queries and long documents. We review the usage of generalized language models, including supervised and unsupervised learning. We observe how our method, while using text summaries, overperforms existing baselines based on full text, and motivate potential improvement directions for future work.
Document type Conference contribution
Language English
Published at https://doi.org/10.3233/FAIA190309
Downloads
FAIA-322-FAIA190309 (Final published version)
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