A methodology for partitioning a vocabulary hierarchy into trees
Document Type
Article
Publication Date
1-1-1999
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.
Publication Title
Artificial Intelligence in Medicine
First Page Number
77
Last Page Number
98
DOI
10.1016/S0933-3657(98)00046-3
Recommended Citation
Gu, Huanying; Perl, Yehoshua; Geller, James; Halper, Michael; and Singh, Mansnimar, "A methodology for partitioning a vocabulary hierarchy into trees" (1999). Kean Publications. 2800.
https://digitalcommons.kean.edu/keanpublications/2800