Identifying mismatches in alignments of large anatomical ontologies

AMIA Annu Symp Proc. 2007 Oct 11;2007:851-5.

Abstract

The objective of this study is to propose a model of matching errors for identifying mismatches in alignments of large anatomical ontologies. Meth-ods: Three approaches to identifying mismatches are utilized: 1) lexical, based on the presence of modifiers in the names of the concepts aligned; 2) structural, identifying conflicting relations resulting from the alignment; and 3) semantic, based on disjoint top-level categories across ontologies.

Results: 83% of the potential mismatches identified by the HMatch system are identified by at least one of the approaches.

Conclusions: Although not a substitute for a careful validation of the matches, these approaches significantly reduce the need for manual validation by effectively characterizing most mismatches.

Publication types

  • Research Support, N.I.H., Intramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Anatomy / classification*
  • Humans
  • Natural Language Processing*
  • Semantics
  • Vocabulary, Controlled*