title: A literature-based assessment of concept pairs as a measure of semantic relatedness.
abstract: The semantic relatedness between two concepts, according to human perception, is domain-rooted and reflects prior knowledge. We developed a new method for semantic relatedness assessment that reflects human judgment, utilizing semantic predications extracted from PubMed citations by SemRep. We compared the new method to other approaches utilizing path-based, statistical, and context vector methods, using a gold standard for evaluation. The new method outperformed all others, except one variation of the context vector technique. These findings have implications in several natural language processing applications, such as serendipitous knowledge discovery.
authors.affiliation: Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD.
authors.forename: T Elizabeth
authors.initials: TE
authors.lastname: Workman
authors.affiliation: Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD.
authors.forename: Graciela
authors.initials: G
authors.lastname: Rosemblat
authors.affiliation: Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD.
authors.forename: Marcelo
authors.initials: M
authors.lastname: Fiszman
authors.affiliation: Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD.
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Rindflesch
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval; D009323:Natural Language Processing; D010820:Physicians; D039781:PubMed; D012660:Semantics; D018709:Statistics, Nonparametric; D013358:Subject Headings; D017432:Unified Medical Language System