Author Name Disambiguation in MEDLINE

By Vetle I. Torvik, Neil R. Smalheiser. TKDD, 2009

299 citations recorded by the source corpus.

Background: We recently described “Author-ity,” a model for estimating the probability that two articles in MEDLINE, sharing the same author name, were written by the same individual. Features include shared title words, journal name, coauthors, medical subject headings, language, affiliations, and author name features (middle initial, suffix, and prevalence in MEDLINE). Here we test the hypothesis that the Author-ity model will suffice to disambiguate author names for the vast majority of articles in MEDLINE. Methods: Enhancements include: (a) incorporating first names and their variants, email addresses, and correlations between specific last names and affiliation words; (b) new methods of generating large unbiased training sets; (c) new methods for estimating the prior probability; (d) a weighted least squares algorithm for correcting transitivity violations; and (e) a maximum likelihood based agglomerative algorithm for computing clusters of articles that represent inferred author-individuals. Results: Pairwise comparisons were computed for all author names on all 15.3 million articles in MEDLINE (2006 baseline), that share last name and first initial, to create Author-ity 2006, a database that has each name on each article assigned to one of 6.7 million inferred author-individual clusters. Recall is estimated at ∼98.8%. Lumping (putting two different individuals into the same cluster) affects ∼0.5% of clusters, whereas splitting (assigning articles written by the same individual to >1 cluster) affects ∼2% of articles. Impact: The Author-ity model can be applied generally to other bibliographic databases. Author name disambiguation allows information retrieval and data integration to become person-centered, not just document-centered, setting the stage for new data mining and social network tools that will facilitate the analysis of scholarly publishing and collaboration behavior. Availability: The Author-ity 2006 database is available for nonprofit academic research, and can be freely queried via http://arrowsmith.psych.uic.edu.

Subfields: Artificial Intelligence, Management Science and Operations Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/152788a40a09cd5b9b979034df608a5cb3909f79

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Citations in the corpus

Collaborating with People Like Me: Ethnic Coauthorship within the United States (2015, unknown): “To check the robustness of our results, we also estimated equation 2 on 2-4 authored papers in Pub Med, which many analysts use in scientometric work because Torvik and Smalheiser (2009) developed a sophisticated algorithm for differentiating same-named people.”
Disambiguation and co-authorship networks of the U.S. patent inventor database (1975–2010) (2014, methodology): “While our work is based mostly on the 2005 Author-ity model (Torvik et al. 2005), more recent work in 2009 (Torvik and Smalheiser 2009) provides a number of suggestions for more rigorously setting parameters like block priors and the weighting coefficient in triplet correction, and for handling…”
PubMed and beyond: a survey of web tools for searching biomedical literature (2011, background): “Authority (59) is another example of specialized systems.”