A Knowledge Representation Model for the Intelligent Retrieval of Legal Cases

Posted: 22 Jun 2008

See all articles by Yiming Zeng

Yiming Zeng

affiliation not provided to SSRN

Ruili Wang

Massey University - Institute of Information Sciences and Technology

John Zeleznikow

Victoria University - Victoria University of Technology

Elizabeth Kemp

affiliation not provided to SSRN

Date Written: Autumn 2007

Abstract

In this paper, we develop a knowledge representation model for the innovative intelligent retrieval of legal cases, which provides effective legal case management. Examples are taken from the domain of accident compensation. A new set of sub-elements for legal case representation (sub-issues, pro-claimant, pro-respondent and contextual features) has been developed to extend the traditional representation elements of issues and factors. In our representation model, an issue may need to be further decomposed into sub-issues; factors are categorised into pro-claimant and pro-respondent factors; and contextual features are also introduced to help retrieval. These extensions can effectively reveal the factual relevance between legal cases. Based on the knowledge representation model, we propose the IPF scheme for intelligent legal case retrieval. Experiment and statistical analysis have been conducted to demonstrate the effectiveness of the proposed representation model and retrieval scheme.

Keywords: Key words: legal case retrieval, case representation elements, legal knowledge representation, accident compensation

Suggested Citation

Zeng, Yiming and Wang, Ruili and Zeleznikow, John and Kemp, Elizabeth, A Knowledge Representation Model for the Intelligent Retrieval of Legal Cases (Autumn 2007). International Journal of Law and Information Technology, Vol. 15, Issue 3, pp. 299-319, 2007. Available at SSRN: https://ssrn.com/abstract=1149600 or http://dx.doi.org/10.1093/ijlit/eal023

Yiming Zeng (Contact Author)

affiliation not provided to SSRN

Ruili Wang

Massey University - Institute of Information Sciences and Technology ( email )

Private Bag 11-222
Palmerston North
New Zealand

John Zeleznikow

Victoria University - Victoria University of Technology ( email )

P.O. Box 14428
Melbourne, Victoria 8001
Australia

Elizabeth Kemp

affiliation not provided to SSRN

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