title: Exploring semantic groups through visual approaches.
abstract: Objectives. We investigate several visual approaches for exploring semantic groups, a grouping of semantic types from the Unified Medical Language System (UMLS) semantic network. We are particularly interested in the semantic coherence of the groups, and we use the semantic relationships as important indicators of that coherence. Methods. First, we create a radial representation of the number of relationships among the groups, generating a profile for each semantic group. Second, we show that, in our partition, the relationships are organized around a limited number of pivot groups and that partitions created at random do not exhibit this property. Finally, we use correspondence analysis to visualize groupings resulting from the association between semantic types and the relationships. Results. The three approaches provide different views on the semantic groups and help detect potential inconsistencies. They make outliers immediately apparent, and, thus, serve as a tool for auditing and validating both the semantic network and the semantic groups.
authors.affiliation: Department of Health and Human Services, National Institutes of Health, National Library of Medicine, Lister Hill National Center for Biomedical Communications, MS 43, Bldg 38A Rm B1N28U, 8600 Rockville Pike, Bethesda, MD 20894, USA. olivier@nlm.nih.gov
authors.forename: Olivier
authors.initials: O
authors.lastname: Bodenreider
authors.forename: Alexa T
authors.initials: AT
authors.lastname: McCray
mesh_terms: D000043:Abstracting and Indexing / Q000379:methods; D000465:Algorithms; D003628:Database Management Systems; D016208:Databases, Factual; D016247:Information Storage and Retrieval / Q000379:methods*; D009317:National Library of Medicine (U.S.); D009323:Natural Language Processing; D012660:Semantics; D009626:Terminology as Topic; D017432:Unified Medical Language System; D014481:United States; D014584:User-Computer Interface