An algorithm for the induction of defeasible logic theories from databases
ADC '03 Proceedings of the 14th Australasian database conference - Volume 17
Induction of defeasible logic theories in the legal domain
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Visualizing association rules for feedback within the legal system
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Maximal Association Rules: A Tool for Mining Associations in Text
Journal of Intelligent Information Systems
Argument based machine learning applied to law
Artificial Intelligence and Law - Argumentation in artificial intelligence and law
Arguing from Experience to Classifying Noisy Data
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
| Hi-index | 0.00 |
The article explores the applicability of an algorithm designed for finding association rules in large databases to the discovery of relevant associations from a large case base. More specifically, it describes an experiment intended to explore the applicability of data mining techniques to legal databases. In many areas of law, especially administrative law, many thousands of cases are decided. This data presents a significant resource. We would generally wish to assume that some rule is being followed so that like cases are decided in a like manner. Is there a way of deciding what the rule being followed is from an automated consideration of the data?.