title: Identifying mismatches in alignments of large anatomical ontologies.
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.
authors.affiliation: Institute of Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, P. R. China. Smzhang@math.ac.cn
authors.forename: Songmao
authors.initials: S
authors.lastname: Zhang
authors.forename: Olivier
authors.initials: O
authors.lastname: Bodenreider
mesh_terms: D000715:Anatomy / Q000145:classification*; D006801:Humans; D009323:Natural Language Processing; D012660:Semantics; D018875:Vocabulary, Controlled