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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
A probabilistic similarity metric for Medline records: a model for author name disambiguation
Vetle I Torvik1, Marc Weeber, Don R Swanson
1Department of Psychiatry, University of Illinois at Chicago, IL, USA.
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).
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