Name
Abstract | ||
|---|---|---|
Case-based reasoning (CBR) systems define knowledge in terms of a memory or library of past cases and a retrieval mechanism that revolves around retrieving data relevant to a goal query. Additionally, such systems employ an adaptation component that transforms the retrieved data into a solution to the problem expressed by the original query. The combination of goal query and the subsequent solution transformation is referred to as CBR goal query. Goal queries are concerned with data that is close to the request expressed in the query. Conventional relational and object-oriented databases are usually concerned specific queries. Extending conventional object-oriented data models, this paper proposes a concept-oriented data model that provides a variety of mechanisms to support conventional goal and CBR goal queries. It is shown that such a concept-oriented data model could be used as the core for a more general knowledge base management system. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1016/S0169-023X(99)00005-1 | Data and Knowledge Engineering |
Keywords | Field | DocType |
Data model,Object-oriented databases,Case-based reasoning,Knowledge representation,Reasoning under uncertainty | Query optimization,Data mining,Web search query,Query language,Query expansion,Information retrieval,Computer science,Sargable,Web query classification,Spatial query,Data model,Database | Journal |
Volume | Issue | ISSN |
30 | 1 | 0169-023X |
Citations | PageRank | References |
9 | 0.74 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Werner Dubitzky | 1 | 435 | 50.31 |
| Alex G. Büchner | 2 | 159 | 13.45 |
| John G. Hughes | 3 | 326 | 59.84 |
| David A. Bell | 4 | 1693 | 305.71 |