title: A probabilistic similarity metric for Medline records: a model for author name disambiguation.
abstract: We present a model for automatically generating training sets and estimating the probability that a pair of Medline records sharing a last and first name initial are authored by the same individual, based on shared title words, journal name, co-authors, medical subject headings, language, and affiliation, as well as distinctive features of the name itself (i.e., presence of middle initial, suffix, and prevalence in Medline).
authors.affiliation: Department of Psychiatry, University of Illinois at Chicago, IL, USA.
authors.forename: Vetle I
authors.initials: VI
authors.lastname: Torvik
authors.forename: Marc
authors.initials: M
authors.lastname: Weeber
authors.forename: Don R
authors.initials: DR
authors.lastname: Swanson
authors.forename: Neil R
authors.initials: NR
authors.lastname: Smalheiser
mesh_terms: D001319:Authorship; D015706:Bibliometrics; D016239:MEDLINE; D046650:Medical Subject Headings; D009275:Names; D011336:Probability