Argument based machine learning applied to law

Artificial Intelligence and Law 13 (1):53-73 (2005)
Abstract
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)
Options
 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: 11,793
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.

Citations of this work BETA
Similar books and articles
Analytics

Monthly downloads

Added to index

2009-01-28

Total downloads

2 ( #361,129 of 1,099,722 )

Recent downloads (6 months)

1 ( #303,379 of 1,099,722 )

How can I increase my downloads?

My notes
Sign in to use this feature


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