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.

Identifier

0032926356 (Scopus)

Publication Title

Artificial Intelligence in Medicine

External Full Text Location

https://doi.org/10.1016/S0933-3657(98)00046-3

ISSN

09333657

PubMed ID

9930617

First Page

77

Last Page

98

Issue

1

Volume

15

Grant

70NANB5H1011

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