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Knowledge Representation for the Intelligent Legal Case Retrieval

Zeng, Yiming, Wang, Ruili, Zeleznikow, John and Kemp, Elizabeth (2005) Knowledge Representation for the Intelligent Legal Case Retrieval. In: Knowledge-Based Intelligent Information and Engineering Systems: 9th International Conference, KES 2005, Melbourne, Australia, September 14-16, 2005, Proceedings. Khosla, Rajiv, Howlett, Robert J and Jain, Lakhmi C, eds. Lecture Notes in Computer Science 0302-9743, 1 (3681). Springer, Berlin, Germany, pp. 339-345.

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Abstract

In this paper, we develop a knowledge representation model for the 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 has been developed to extend the traditional representation elements of issues and factors. In our model, an issue may need to be further decomposed into sub-issues, and factors are categorized into pro-claimant, pro-responder and neutral factors. These extensions can effectively reveal the factual relevance between legal cases. Based on the knowledge representation model, we propose the IPN algorithm for intelligent legal case retrieval. Experiments and statistical analysis have been conducted to demonstrate the effectiveness of the proposed representation model and the IPN algorithm.

Item Type: Book Section
ISBN: 9783540288947 (print) 9783540319832 (online)
Additional Information:

KES 2005, LNAI 3681

Uncontrolled Keywords: ResPubID8598 precedent, cased-based retrieval, legal case-based reasoning, HYPO model, CATO model, algorithm
Subjects: RFCD Classification > 280000 Information, Computing and Communication Sciences
FOR Classification > 0801 Artificial Intelligence and Image Processing
FOR Classification > 0806 Information Systems
FOR Classification > 1801 Law
Faculty/School/Research Centre/Department > School of Management and Information Systems
Depositing User: VUIR
Date Deposited: 17 Sep 2013 06:38
Last Modified: 17 Sep 2013 06:38
URI: http://vuir.vu.edu.au/id/eprint/10652
DOI: https://doi.org/10.1007/11552413_49
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Citations in Scopus: 5 - View on Scopus

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