Name
Abstract | ||
|---|---|---|
Case adaptation continues to be one of the more difficult aspects of case-based reasoning to automate. This paper looks at several techniques for utilising the implicit knowledge contained in a case base for case adaptation in case-based reasoning systems. The most significant of the techniques proposed are a moderately successful data mining technique and a highly successful artificial neural network technique. Their effectiveness was evaluated on a footwear design problem. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-76928-6_59 | Australian Conference on Artificial Intelligence |
Keywords | Field | DocType |
successful data mining technique,difficult aspect,adaptation knowledge,successful artificial neural network,case base,implicit knowledge,case-based reasoning,footwear design problem,case-based reasoning system,case adaptation,artificial neural network,data mining,case base reasoning | Computer science,Implicit knowledge,Model-based reasoning,Case base,Artificial intelligence,Artificial neural network,Machine learning | Conference |
Volume | ISSN | ISBN |
4830 | 0302-9743 | 3-540-76926-9 |
Citations | PageRank | References |
1 | 0.35 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julie Main | 1 | 12 | 2.32 |
| Tharam S. Dillon | 2 | 2573 | 340.98 |
| Mary Witten | 3 | 3 | 0.72 |