Abstract
Case Base Reasoning (CBR), which is characterized by its capability to capture past experience and knowledge for case matching in various applications, is an emerging and well-accepted approach in the implementation Knowledge Management (KM) systems. The data format of CBR belongs to the 'free' type and therefore is dissimilar to the traditional relational data model which emphasizes on specified data fields, field lengths and data types. However, there is a lack of research regarding the seamless integration of these heterogeneous data models for achieving effective data communication, which is essential to enhance business workflow of enterprises. This paper attempts to propose an integrated knowledge system to support the extrapolation of projected outcomes of events based on knowledge generated by the relational database model and CBR knowledge model, both of which supplement and complement each other by virtue of their distinct structural features. © 2002 Published by Elsevier Science B.V.
| Original language | English |
|---|---|
| Pages (from-to) | 69-76 |
| Journal | Knowledge-Based Systems |
| Volume | 16 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Mar 2003 |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Research Keywords
- Case base reasoning
- Data warehouse
- Knowledge management
- Online analytical processing
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