title: Semantic Similarity and Relatedness between Clinical Terms: An Experimental Study.
abstract: Automated approaches to measuring semantic similarity and relatedness can provide necessary semantic context information for information retrieval applications and a number of fundamental natural language processing tasks including word sense disambiguation. Challenges for the development of these approaches include the limited availability of validated reference standards and the need for better understanding of the notions of semantic relatedness and similarity in medical vocabulary. We present results of a study in which eight medical residents were asked to judge 724 pairs of medical terms for semantic similarity and relatedness. The results of the study confirm the existence of a measurable mental representation of semantic relatedness between medical terms that is distinct from similarity and independent of the context in which the terms occur. This study produced a validated publicly available dataset for developing automated approaches to measuring semantic relatedness and similarity.
authors.affiliation: College of Pharmacy, University of Minnesota, MN, USA.
authors.forename: Serguei
authors.initials: S
authors.lastname: Pakhomov
authors.forename: Bridget
authors.initials: B
authors.lastname: McInnes
authors.forename: Terrence
authors.initials: T
authors.lastname: Adam
authors.forename: Ying
authors.initials: Y
authors.lastname: Liu
authors.forename: Ted
authors.initials: T
authors.lastname: Pedersen
authors.forename: Genevieve B
authors.initials: GB
authors.lastname: Melton
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval; D009323:Natural Language Processing; D012660:Semantics; D014825:Vocabulary