A Knowledge Representation Model for the Intelligent Retrieval of Legal Cases |
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Authors: | Zeng, Yiming Wang, Ruili Zeleznikow, John Kemp, Elizabeth |
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Affiliation: | 1 Institute of Information Sciences and Technology, Massey University, New Zealand E-mail: y.zeng{at}massey.ac.nz |
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Abstract: | In this paper, we develop a knowledge representation model forthe innovative intelligent retrieval of legal cases, which provideseffective legal case management. Examples are taken from thedomain of accident compensation. A new set of sub-elements forlegal case representation (sub-issues, pro-claimant, pro-respondentand contextual features) has been developed to extend the traditionalrepresentation elements of issues and factors. In our representationmodel, an issue may need to be further decomposed into sub-issues;factors are categorised into pro-claimant and pro-respondentfactors; and contextual features are also introduced to helpretrieval. These extensions can effectively reveal the factualrelevance between legal cases. Based on the knowledge representationmodel, we propose the IPF scheme for intelligent legal caseretrieval. Experiment and statistical analysis have been conductedto demonstrate the effectiveness of the proposed representationmodel and retrieval scheme. |
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Keywords: | Key words: legal case retrieval case representation elements legal knowledge representation accident compensation |
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