Abstract
Controlled medical vocabularies are useful in application areas such as medical information systems and decision-support systems. However, such vocabularies are large and complex, and working with them can be daunting. It is important to provide a means for orienting vocabulary designers and users to the vocabulary's contents. We describe a methodology for partitioning a vocabulary based on the IS-A hierarchy into small meaningful pieces. The methodology uses our disciplined modeling framework to refine the IS-A hierarchy according to prescribed rules in a process carried out by a user in conjunction with the computer. The partitioning of the hierarchy implies a partitioning of the vocabulary. We demonstrate the methodology with respect to a complex sample of the MED, an existing medical vocabulary.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 77-98 |
| Number of pages | 22 |
| Journal | Artificial Intelligence in Medicine |
| Volume | 15 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1999 |
All Science Journal Classification (ASJC) codes
- Medicine (miscellaneous)
- Artificial Intelligence
Keywords
- Controlled medical vocabulary
- Object-oriented modeling
- Ontology
- Partitioning
- Semantic network