Name
Abstract | ||
|---|---|---|
Being based on the concept hierarchy, the paper has introduced a new kind of knowledge representation into the system of data mining which can help transfer the concept hierarchy into a range of decision tables. While taking into account the relationship among the nodes at different levels of a concept hierarchy, the paper further proposed a hierarchical reduction algorithm which can be used for the reduction of both attributes and values in the decision tables. At the same time to theoretically prove the rationality of the algorithm, the paper has furthermore proved its efficiency and reliability with an empirical study of the Microelectromechanical System. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ISDA.2006.59 | ISDA (1) |
Keywords | Field | DocType |
knowledge representation,decision tables,data mining,decision table,empirical study | Knowledge representation and reasoning,Decision table,Rationality,Computer science,Algorithm,Artificial intelligence,Machine learning,Empirical research,Concept hierarchy | Conference |
Volume | Issue | ISBN |
1 | null | 0-7695-2528-8 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junpeng Yuan | 1 | 17 | 2.15 |
| Donghua Zhu | 2 | 40 | 6.32 |