title: A methodology for extending domain coverage in SemRep.
abstract: We describe a domain-independent methodology to extend SemRep coverage beyond the biomedical domain. SemRep, a natural language processing application originally designed for biomedical texts, uses the knowledge sources provided by the Unified Medical Language System (UMLS©). Ontological and terminological extensions to the system are needed in order to support other areas of knowledge. We extended SemRep's application by developing a semantic representation of a previously unsupported domain. This was achieved by adapting well-known ontology engineering phases and integrating them with the UMLS knowledge sources on which SemRep crucially depends. While the process to extend SemRep coverage has been successfully applied in earlier projects, this paper presents in detail the step-wise approach we followed and the mechanisms implemented. A case study in the field of medical informatics illustrates how the ontology engineering phases have been adapted for optimal integration with the UMLS. We provide qualitative and quantitative results, which indicate the validity and usefulness of our methodology.
authors: National Library of Medicine, National Institutes of Health, Lister Hill Center, Cognitive Science Branch, 8600 Rockville Pike, Bethesda, MD 20894, USA. Electronic address: grosemblat@mail.nih.gov.
authors: Graciela
authors: G
authors: Rosemblat
authors: Dongwook
authors: D
authors: Shin
authors: Halil
authors: H
authors: Kilicoglu
authors: Charles
authors: C
authors: Sneiderman
authors: Thomas C
authors: TC
authors: Rindflesch
mesh_terms: D016247:Information Storage and Retrieval; D009323:Natural Language Processing; D012660:Semantics; D017432:Unified Medical Language System
keywords: Domain-independent ontology development methodology; Natural language processing application; Semantic predications; UMLS knowledge sources
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