Argument based machine learning applied to law

Artificial Intelligence and Law 13 (1):53-73 (2005)
In this paper we discuss the application of a new machine learning approach – Argument Based Machine Learning – to the legal domain. An experiment using a dataset which has also been used in previous experiments with other learning techniques is described, and comparison with previous experiments made. We also tested this method for its robustness to noise in learning data. Argumentation based machine learning is particularly suited to the legal domain as it makes use of the justifications of decisions which are available. Importantly, where a large number of decided cases are available, it provides a way of identifying which need to be considered. Using this technique, only decisions which will have an influence on the rules being learned are examined.
Keywords argumentation  legal information systems  legal knowledge discovery  machine learning  rule induction
Categories (categorize this paper)
DOI 10.1007/s10506-006-9002-4
 Save to my reading list
Follow the author(s)
My bibliography
Export citation
Find it on Scholar
Edit this record
Mark as duplicate
Revision history Request removal from index
Download options
PhilPapers Archive

Upload a copy of this paper     Check publisher's policy on self-archival     Papers currently archived: 20,010
External links
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library
References found in this work BETA

No references found.

Add more references

Citations of this work BETA

Add more citations

Similar books and articles

Monthly downloads

Added to index


Total downloads

36 ( #109,632 of 1,793,059 )

Recent downloads (6 months)

26 ( #29,364 of 1,793,059 )

How can I increase my downloads?

My notes
Sign in to use this feature

Start a new thread
There  are no threads in this forum
Nothing in this forum yet.