Semi-Supervised Methods for Explainable Legal Prediction-Reference-Cited by-同舟云学术

Semi-Supervised Methods for Explainable Legal Prediction

Published:2019-06-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law
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Author:

Branting K.¹,Weiss B.¹,Brown B.¹,Pfeifer C.²,Chakraborty A.³,Ferro L.³,Pfaff M.³,Yeh A.³

Affiliation:

1. The MITRE Corporation, McLean, VA, USA

2. The MITRE Corporation, Ann Arbor, MI, USA

3. The MITRE Corporation, Bedford, MA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3322640.3326723

Reference36 articles.

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2. Aletras N. Tsarapatsanis D. Preotiuc-Pietro D. Lampos V.: Predicting judicial decisions of the European Court of Human Rights: a natural language processing perspective. PeerJ CompSci (October 24 2016) https://peerj.com/articles/cs-93/ Aletras N. Tsarapatsanis D. Preotiuc-Pietro D. Lampos V.: Predicting judicial decisions of the European Court of Human Rights: a natural language processing perspective. PeerJ CompSci (October 24 2016) https://peerj.com/articles/cs-93/

3. Evaluating a learning environment for case-based argumentation skills

4. Aleven V.A.W.M.M.: Teaching Case-based Argumentation Through a Model and Examples. Ph.D. thesis University of Pittsburgh Pittsburgh PA USA (1997) aAI9821228 Aleven V.A.W.M.M.: Teaching Case-based Argumentation Through a Model and Examples. Ph.D. thesis University of Pittsburgh Pittsburgh PA USA (1997) aAI9821228

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