Name
Abstract | ||
|---|---|---|
Case-Based Reasoning (CBR) can be seen as a problem-solving paradigm that advocates the use of previous experiences to limit search spaces and to reduce opportunities for error repetition. In this paradigm, the case at hand is compared against former experiences to select from a set of possible courses of action the best one. A comparison method is required to ensure that the most resembling experience is, in fact, chosen to drive the problem-solving process. This paper discusses an object-oriented framework that provides a scale-guided measure of similarity between objects, and shows how this framework can be applied for case-based reasoning, drawing examples from device diagnosis. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1007/BF01258210 | Journal of Intelligent and Robotic Systems |
Keywords | Field | DocType |
Case-based reasoning,object-oriented methods,device diagnosis,similarity,analogy,associative data bases | Object oriented methods,Computer science,Adaptive reasoning,Model-based reasoning,Object matching,Artificial intelligence,Analogy,Case-based reasoning,Reasoning system,Machine learning,Qualitative reasoning | Journal |
Volume | Issue | ISSN |
7 | 1 | 0921-0296 |
Citations | PageRank | References |
1 | 0.57 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan E. Vargas | 1 | 6 | 2.46 |
| John R. Bourne | 2 | 21 | 8.49 |