Standard
Re-Framing Case Law Citation Prediction from a Paragraph Perspective. / Olsen, Henrik Palmer; Garneau, Nicolas; Panagis, Yannis; Lindholm, Johan; Søgaard, Anders.
Legal Knowledge and Information Systems - JURIX 2023: 36th Annual Conference. ed. / Giovanni Sileno; Jerry Spanakis; Gijs van Dijck. IOS Press BV, 2023. p. 323-328 (Frontiers in Artificial Intelligence and Applications, Vol. 379).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Olsen, HP, Garneau, N, Panagis, Y, Lindholm, J
& Søgaard, A 2023,
Re-Framing Case Law Citation Prediction from a Paragraph Perspective. in G Sileno, J Spanakis & G van Dijck (eds),
Legal Knowledge and Information Systems - JURIX 2023: 36th Annual Conference. IOS Press BV, Frontiers in Artificial Intelligence and Applications, vol. 379, pp. 323-328, 36th International Conference on Legal Knowledge and Information Systems, JURIX 2023, Maastricht, Netherlands,
18/12/2023.
https://doi.org/10.3233/FAIA230982
APA
Olsen, H. P., Garneau, N., Panagis, Y., Lindholm, J.
, & Søgaard, A. (2023).
Re-Framing Case Law Citation Prediction from a Paragraph Perspective. In G. Sileno, J. Spanakis, & G. van Dijck (Eds.),
Legal Knowledge and Information Systems - JURIX 2023: 36th Annual Conference (pp. 323-328). IOS Press BV. Frontiers in Artificial Intelligence and Applications Vol. 379
https://doi.org/10.3233/FAIA230982
Vancouver
Olsen HP, Garneau N, Panagis Y, Lindholm J
, Søgaard A.
Re-Framing Case Law Citation Prediction from a Paragraph Perspective. In Sileno G, Spanakis J, van Dijck G, editors, Legal Knowledge and Information Systems - JURIX 2023: 36th Annual Conference. IOS Press BV. 2023. p. 323-328. (Frontiers in Artificial Intelligence and Applications, Vol. 379).
https://doi.org/10.3233/FAIA230982
Author
Olsen, Henrik Palmer ; Garneau, Nicolas ; Panagis, Yannis ; Lindholm, Johan ; Søgaard, Anders. / Re-Framing Case Law Citation Prediction from a Paragraph Perspective. Legal Knowledge and Information Systems - JURIX 2023: 36th Annual Conference. editor / Giovanni Sileno ; Jerry Spanakis ; Gijs van Dijck. IOS Press BV, 2023. pp. 323-328 (Frontiers in Artificial Intelligence and Applications, Vol. 379).
Bibtex
@inproceedings{33d24df886604e25b657797ab5e754e9,
title = "Re-Framing Case Law Citation Prediction from a Paragraph Perspective",
abstract = "Case law citation prediction, i.e., predicting what historical cases are relevant for your current case, can assist legal discovery and decision-making, but legal documents are long, and often only parts of them are relevant for a particular use case. We therefore reframe case law citation prediction as a paragraph-to-paragraph citation task, introduce a new dataset, and train and evaluate new models. We also evaluate our models qualitatively. Our resources provide a first step toward discovering citation patterns and modeling legal rules in EU law from precedent documents. ",
keywords = "case law citation, legal dataset, legal rules, link prediction",
author = "Olsen, {Henrik Palmer} and Nicolas Garneau and Yannis Panagis and Johan Lindholm and Anders S{\o}gaard",
note = "Publisher Copyright: {\textcopyright} 2023 The Authors.; 36th International Conference on Legal Knowledge and Information Systems, JURIX 2023 ; Conference date: 18-12-2023 Through 20-12-2023",
year = "2023",
doi = "10.3233/FAIA230982",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "323--328",
editor = "Giovanni Sileno and Jerry Spanakis and {van Dijck}, Gijs",
booktitle = "Legal Knowledge and Information Systems - JURIX 2023",
address = "Netherlands",
}
RIS
TY - GEN
T1 - Re-Framing Case Law Citation Prediction from a Paragraph Perspective
AU - Olsen, Henrik Palmer
AU - Garneau, Nicolas
AU - Panagis, Yannis
AU - Lindholm, Johan
AU - Søgaard, Anders
N1 - Publisher Copyright:
© 2023 The Authors.
PY - 2023
Y1 - 2023
N2 - Case law citation prediction, i.e., predicting what historical cases are relevant for your current case, can assist legal discovery and decision-making, but legal documents are long, and often only parts of them are relevant for a particular use case. We therefore reframe case law citation prediction as a paragraph-to-paragraph citation task, introduce a new dataset, and train and evaluate new models. We also evaluate our models qualitatively. Our resources provide a first step toward discovering citation patterns and modeling legal rules in EU law from precedent documents.
AB - Case law citation prediction, i.e., predicting what historical cases are relevant for your current case, can assist legal discovery and decision-making, but legal documents are long, and often only parts of them are relevant for a particular use case. We therefore reframe case law citation prediction as a paragraph-to-paragraph citation task, introduce a new dataset, and train and evaluate new models. We also evaluate our models qualitatively. Our resources provide a first step toward discovering citation patterns and modeling legal rules in EU law from precedent documents.
KW - case law citation
KW - legal dataset
KW - legal rules
KW - link prediction
U2 - 10.3233/FAIA230982
DO - 10.3233/FAIA230982
M3 - Article in proceedings
AN - SCOPUS:85181165382
T3 - Frontiers in Artificial Intelligence and Applications
SP - 323
EP - 328
BT - Legal Knowledge and Information Systems - JURIX 2023
A2 - Sileno, Giovanni
A2 - Spanakis, Jerry
A2 - van Dijck, Gijs
PB - IOS Press BV
T2 - 36th International Conference on Legal Knowledge and Information Systems, JURIX 2023
Y2 - 18 December 2023 through 20 December 2023
ER -
