A legal ontology refinement support environment using a machine-readable dictionary

Artificial Intelligence and Law 5 (1-2):119-137 (1997)

Abstract
This paper discusses how to refine a given initial legal ontology using an existing MRD (Machine-Readable Dictionary). There are two hard issues in the refinement process. One is to find out those MRD concepts most related to given legal concepts. The other is to correct bugs in a given legal ontology, using the concepts extracted from an MRD. In order to resolve the issues, we present a method to find out the best MRD correspondences to given legal concepts, using two match algorithms. Moreover, another method called a static analysis is given to refine a given legal ontology, based on the comparison between the initial legal ontology and the best MRD correspondences to given legal concepts. We have implemented a software environment to help a user refine a given legal ontology based on these methods. The empirical results have shown that the environment works well in the field of Contracts for the International Sale of Goods.
Keywords ontology refinement  legal ontologies  machine-readable dictionaries  spell match  definition match  static analysis  Contracts for the International Sale of Goods
Categories (categorize this paper)
DOI 10.1023/A:1008220029904
Options
Edit this record
Mark as duplicate
Export citation
Find it on Scholar
Request removal from index
Revision history

Download options

Our Archive


Upload a copy of this paper     Check publisher's policy     Papers currently archived: 45,662
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

No citations found.

Add more citations

Similar books and articles

Analytics

Added to PP index
2009-01-28

Total views
43 ( #205,073 of 2,280,728 )

Recent downloads (6 months)
6 ( #194,568 of 2,280,728 )

How can I increase my downloads?

Downloads

My notes

Sign in to use this feature