Entropy in Legal Language

Download
Full text (accepted version) (PDF, 985.6Kb)
Thumbnail
Open access
ccby
Autor(in)
Friedrich, Roland
Luzzatto, Mauro
Ash, Elliott
Datum
2020-08
Typ
    Conference Paper
Rechte / Lizenz
Creative Commons Attribution 4.0 International
Persistenter Link
https://doi.org/10.3929/ethz-b-000427800
Publikationsstatus
published
Herausgeber(in)
Aletras, Nikolaos
Androutsopoulos, Ion
Barrett, Leslie
Meyers, Adam
Preoţiuc-Pietro, Daniel
Buchtitel
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)
Zeitschrift / Serie
CEUR Workshop Proceedings
Band
2645
Seiten / Artikelnummer
25 - 30
Verlag
CEUR-WS
Konferenz
2nd Workshop on Natural Legal Language Processing (NLLP, collocated with KDD 2020) (virtual), San Diego, CA, USA, August 24, 2020
Thema
Computing methodologies; Markov processes; Coding theory; Neural language models; NLP; word2vec; Entropy; Civil law; Common law; Judiciary; Comparative law
Organisationseinheit
09627 - Ash, Elliott / Ash, Elliott  
Anmerkungen
Conference lecture on August 24, 2020. Due to the Coronavirus (COVID-19) the conference was conducted virtually.
Mehr
Alle Metadaten anzeigen
ETH Bibliographie
yes
Altmetrics