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.

We are conducting a project to build a knowledge infrastructure to improve common understandings and knowledge among doctors, patients and researchers. The knowledge infrastructure consists of terms and semantic relationships among them, represented using the hypernetwork model. In order to build a merged knowledge representation, the terms used by the patients and doctors/researchers were analyzed. Less than fifth of terms were common, indicating differences in viewpoints.