Research on Scalable Case Representation and Its Retrieval Based on Description Logic

In recent years, the combination of case-based reasoning (CBR) and domain knowledge has become a hotspot in CBR field. Different knowledge representation ways bring about different influences of CBR system performance. This paper makes a summarization and an analysis of deficiencies in integration between traditional knowledge representation and CBR, based on which it proposes a scalable case representation model using description logic (DL). Moreover, the corresponding case retrieval algorithm is also presented. The domain knowledge in CBR system mainly serves for the case retrieval and revision. Furthermore, the integration usage of domain-knowledge should be determined according to the actual demand and application background .These are the focus of emphasis of the presented model .Keeping the CBR system´s merits, the model provides a approach to flexible use of domain knowledge.