Name
Abstract | ||
|---|---|---|
This paper presents a hierarchical case representation using a context guided retrieval method. The performance of this method is compared to that of a simpler flat file representation using standard nearest neighbour retrieval. The estimation of construction costs of light industrial buildings is used as the test domain. Each case in the system has approximately 400 features. These are structured into a hierarchical case representation that holds more general contextual features at its top and specific building elements at its leaves. Problems are decomposed into sub-problems and solutions recomposed into a final solution. Comparative results show that the context guided retrieval method using the hierarchical case representation is significantly more accurate than the simpler flat file representation using standard nearest neighbour retrieval. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1016/S0950-7051(98)00068-9 | Knowledge-Based Systems |
Keywords | Field | DocType |
Case-based reasoning,Case-representation,Context guided retrieval | Data mining,Nearest neighbour,Computer science,Flat file database,Theoretical computer science,Artificial intelligence,Case-based reasoning,Machine learning | Journal |
Volume | Issue | ISSN |
11 | 5-6 | 0950-7051 |
Citations | PageRank | References |
11 | 0.84 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ian Watson | 1 | 1092 | 66.10 |
| Srinath Perera | 2 | 332 | 32.23 |