Recognizing cited facts and principles in legal judgements
- Submitting institution
-
The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1461139
- Type
- D - Journal article
- DOI
-
10.1007/s10506-017-9197-6
- Title of journal
- Artificial Intelligence and Law
- Article number
- -
- First page
- 107
- Volume
- 25
- Issue
- 1
- ISSN
- 0924-8463
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 12
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Common law follows the doctrine of "stare decisis", whereby cases with similar facts should receive similar decisions following similar legal principles. Legal professionals spend considerable effort identifying such facts and principles from precedent cases. This article is significant for its demonstration that the process can be automated through supervised machine learning. Other groups directly build on this article (Valvoda and Ray 2017; Cao et al. 2020; Bhattacharya et al. 2019), which is also widely cited by papers applying similar text mining approaches to judicial texts for other purposes, such as predicting court decisions and detecting unfair clauses in consumer contracts.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -