title: Suggesting Missing Relations in Biomedical Ontologies Based on Lexical Regularities.
abstract: The number of biomedical ontologies has increased significantly in recent years. Many of such ontologies are the result of efforts of communities of domain experts and ontology engineers. The development and application of quality assurance (QA) methods should help these communities to develop useful ontologies for both humans and machines. According to previous studies, biomedical ontologies are rich in natural language content, but most of them are not so rich in axiomatic terms. Here, we are interested in studying the relation between content in natural language and content in axiomatic form. The analysis of the labels of the classes permits to identify lexical regularities (LRs), which are sets of words that are shared by labels of different classes. Our assumption is that the classes exhibiting an LR should be logically related through axioms, which is used to propose an algorithm to detect missing relations in the ontology. Here, we analyse a lexical regularity of SNOMED CT, congenital stenosis, which is reported as problematic by the SNOMED CT maintenance team.
authors: Facultad de Informática, Universidad de Murcia, IMIB-Arrixaca, CP 30100 Murcia.
authors: Manuel
authors: M
authors: Quesada-Martínez
authors: Facultad de Informática, Universidad de Murcia, IMIB-Arrixaca, CP 30100 Murcia.
authors: Jesualdo Tomás
authors: JT
authors: Fernández-Breis
authors: Department of Biomedical Engineering, Linköping University, Sweden.
authors: Daniel
authors: D
authors: Karlsson
mesh_terms: D001024:Aortic Valve Stenosis / Q000151:congenital; D064229:Biological Ontologies; D007802:Language; D009323:Natural Language Processing; D039061:Systematized Nomenclature of Medicine