David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Artificial Intelligence and Law 16 (4):361-387 (2008)
The paper gives ontologies in the Web Ontology Language (OWL) for Legal Case-based Reasoning (LCBR) systems, giving explicit, formal, and general specifications of a conceptualisation LCBR. Ontologies for different systems allows comparison and contrast between them. OWL ontologies are standardised, machine-readable formats that support automated processing with Semantic Web applications. Intermediate concepts, concepts between base-level concepts and higher level concepts, are central in LCBR. The main issues and their relevance to ontological reasoning and to LCBR are discussed. Two LCBR systems (AS-CATO, which is based on CATO, and IBP) are analysed in terms of basic and intermediate concepts. Central components of the OWL ontologies for these systems are presented, pointing out differences and similarities. The main novelty of the paper is the ontological analysis and representation in OWL of LCBR systems. The paper also emphasises the important issues concerning the representation and reasoning of intermediate concepts.
|Keywords||OWL Ontology Legal reasoning Legal cases Case-based reasoning|
|Categories||categorize this paper)|
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
Trevor Bench-Capon, Michał Araszkiewicz, Kevin Ashley, Katie Atkinson, Floris Bex, Filipe Borges, Daniele Bourcier, Paul Bourgine, Jack G. Conrad, Enrico Francesconi, Thomas F. Gordon, Guido Governatori, Jochen L. Leidner, David D. Lewis, Ronald P. Loui, L. Thorne McCarty, Henry Prakken, Frank Schilder, Erich Schweighofer, Paul Thompson, Alex Tyrrell, Bart Verheij, Douglas N. Walton & Adam Z. Wyner (2012). A History of AI and Law in 50 Papers: 25 Years of the International Conference on AI and Law. [REVIEW] Artificial Intelligence and Law 20 (3):215-319.
Adam Wyner & Rinke Hoekstra (2012). A Legal Case OWL Ontology with an Instantiation of Popov V. Hayashi. Artificial Intelligence and Law 20 (1):83-107.
Similar books and articles
Jos Lehmann & Aldo Gangemi (2007). An Ontology of Physical Causation as a Basis for Assessing Causation in Fact and Attributing Legal Responsibility. Artificial Intelligence and Law 15 (3):301-321.
Pepijn R. S. Visser & Trevor J. M. Bench-Capon (1998). A Comparison of Four Ontologies for the Design of Legal Knowledge Systems. Artificial Intelligence and Law 6 (1):27-57.
John Zeleznikow, George Vossos & Daniel Hunter (1993). The IKBALS Project: Multi-Modal Reasoning in Legal Knowledge Based Systems. [REVIEW] Artificial Intelligence and Law 2 (3):169-203.
Masaki Kurematsu & Takahira Yamaguchi (1997). A Legal Ontology Refinement Support Environment Using a Machine-Readable Dictionary. Artificial Intelligence and Law 5 (1-2):119-137.
Mariano Rodr´Iguez, Toward Using Bio-Ontologies in the Semantic Web: Trade-Offs Between Ontology Languages.
Joost Breuker, André Valente & Radboud Winkels (2004). Legal Ontologies in Knowledge Engineering and Information Management. Artificial Intelligence and Law 12 (4):241-277.
José Saias & Paulo Quaresma (2004). A Methodology to Create Legal Ontologies in a Logic Programming Based Web Information Retrieval System. Artificial Intelligence and Law 12 (4):397-417.
Added to index2009-01-28
Total downloads27 ( #75,901 of 1,689,873 )
Recent downloads (6 months)3 ( #78,763 of 1,689,873 )
How can I increase my downloads?