title: U-path: An undirected path-based measure of semantic similarity.
abstract: In this paper, we present the results of a method using undirected paths to determine the degree of semantic similarity between two concepts in a dense taxonomy with multiple inheritance. The overall objective of this work was to explore methods that take advantage of dense multi-hierarchical taxonomies that are more graph-like than tree-like by incorporating the proximity of concepts with respect to each other within the entire is-a hierarchy. Our hypothesis is that the proximity of the concepts regardless of how they are connected is an indicator to the degree of their similarity. We evaluate our method using the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), and four reference standards that have been manually tagged by human annotators. The overall results of our experiments show, in SNOMED CT, the location of the concepts with respect to each other does indicate the degree to which they are similar.
authors.affiliation: Virginia Commonwealth University, Richmond, VA.
authors.forename: Bridget T
authors.initials: BT
authors.lastname: McInnes
authors.affiliation: University of Minnesota, Duluth, MN.
authors.forename: Ted
authors.initials: T
authors.lastname: Pedersen
authors.affiliation: The Advisory Board Company, San Francisco, CA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Liu
authors.affiliation: University of Minnesota, Minneapolis, MN.
authors.forename: Genevieve B
authors.initials: GB
authors.lastname: Melton
authors.affiliation: University of Minnesota, Minneapolis, MN.
authors.forename: Serguei V
authors.initials: SV
authors.lastname: Pakhomov
mesh_terms: D006801:Humans; D012015:Reference Standards; D012660:Semantics; D018709:Statistics, Nonparametric; D039061:Systematized Nomenclature of Medicine; D017432:Unified Medical Language System; D018875:Vocabulary, Controlled