A methodology for partitioning a vocabulary hierarchy into trees

Huanying Gu, Yehoshua Perl, James Geller, Michael Halper, Mansnimar Singh

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

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 languageEnglish (US)
Pages (from-to)77-98
Number of pages22
JournalArtificial Intelligence in Medicine
Volume15
Issue number1
DOIs
StatePublished - Jan 1999

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Artificial Intelligence

Keywords

  • Controlled medical vocabulary
  • Object-oriented modeling
  • Ontology
  • Partitioning
  • Semantic network

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