Name
Abstract | ||
|---|---|---|
We address the problem of generalizing temporal dataconcerning durations extracted from relational databases.Our approach is based on a domain generalizationgraph that defines a partial order specifying thegeneralization relations for a duration attribute. Thisdomain generalization graph is reusable (i.e., can beused to generalize any duration attribute), adaptable(i.e., can be extended or restricted as appropriate forparticular applications), and transportable (i.e., canbe... |
Year | Venue | Keywords |
|---|---|---|
1998 | FLAIRS Conference | relational databases,generalizing temporal durations,partial order,relational database |
Field | DocType | ISBN |
Graph,Relational database,Generalization,Computer science,Algorithm,Temporal database,Artificial intelligence,Granularity,Machine learning,Attribute domain | Conference | 1-57735-051-0 |
Citations | PageRank | References |
3 | 0.51 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dee Jay Randall | 1 | 34 | 4.17 |
| Howard J. Hamilton | 2 | 1501 | 145.55 |
| Robert J. Hilderman | 3 | 270 | 29.86 |