2006, English, Article, Review edition: A Knowledge Representation Model for the Intelligent Retrieval of Legal Cases Zeng, Yiming; Wang, Ruili; Zeleznikow, John; ...

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Physical Description
  • journal article
  • PeerReviewed
Published
  • Oxford University Press, 2006
Language
  • English

Edition details

Title
  • A Knowledge Representation Model for the Intelligent Retrieval of Legal Cases
Author
  • Zeng, Yiming
  • Wang, Ruili
  • Zeleznikow, John
  • Kemp, Elizabeth
Published
  • Oxford University Press, 2006
Physical Description
  • journal article
  • PeerReviewed
Subjects
Summary
  • 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.
Language
  • English
Related Resource
Identifier
  • oai:eprints.vu.edu.au:3137
  • Zeng, Yiming and Wang, Ruili and Zeleznikow, John and Kemp, Elizabeth (2006) A Knowledge Representation Model for the Intelligent Retrieval of Legal Cases. International Journal of Law and Information Technology, 15 (3). pp. 299-319. ISSN 1464-3693

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