Entropy in Legal Language

Download
Full text (accepted version) (PDF, 985.6Kb)
Thumbnail
Open access
ccby
Author
Friedrich, Roland
Luzzatto, Mauro
Ash, Elliott
Date
2020-08
Type
    Conference Paper
Rights / license
Creative Commons Attribution 4.0 International
Permanent link
https://doi.org/10.3929/ethz-b-000427800
Publication status
published
Editor
Aletras, Nikolaos
Androutsopoulos, Ion
Barrett, Leslie
Meyers, Adam
Preoţiuc-Pietro, Daniel
Book title
NLLP 2020 Natural Legal Language Processing Workshop 2020. Proceedings of the Natural Legal Language Processing Workshop 2020 co-located with the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020)
Journal / series
CEUR Workshop Proceedings
Volume
2645
Pages / Article No.
25 - 30
Publisher
CEUR-WS
Event
2nd Workshop on Natural Legal Language Processing (NLLP, collocated with KDD 2020) (virtual), San Diego, CA, USA, August 24, 2020
Subject
Computing methodologies; Markov processes; Coding theory; Neural language models; NLP; word2vec; Entropy; Civil law; Common law; Judiciary; Comparative law
Organisational unit
09627 - Ash, Elliott / Ash, Elliott  
Notes
Conference lecture on August 24, 2020. Due to the Coronavirus (COVID-19) the conference was conducted virtually.
More
Show all metadata
ETH Bibliography
yes
Altmetrics