Name
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1093/ijlit/eal023 | INTERNATIONAL JOURNAL OF LAW AND INFORMATION TECHNOLOGY |
Keywords | Field | DocType |
legal case retrieval, case representation elements, legal knowledge representation, accident compensation | Information system,Knowledge representation and reasoning,Legal case,Information retrieval,Computer science,Computer security,Knowledge management,Statistical analysis | Journal |
Volume | Issue | ISSN |
15 | 3 | 0967-0769 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yiming Zeng | 1 | 25 | 2.61 |
| Ruili Wang | 2 | 446 | 50.35 |
| john zeleznikow | 3 | 513 | 77.54 |
| Elizabeth A. Kemp | 4 | 45 | 7.30 |