Data sets for author name disambiguation: an empirical analysis and a new resource.

Autor/inn/en	Müller, Mark-Christoph; Reitz, Florian; Roy, Nicolas
Titel	Data sets for author name disambiguation: an empirical analysis and a new resource.
Quelle	In: Scientometrics, (2017) 3, S.1467-1500 PDF als Volltext Verfügbarkeit
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0138-9130
DOI	10.1007/s11192-017-2363-5
Schlagwörter	Author name disambiguation; Author name homography; Author name variability; Data sets; Digital libraries
Abstract	Abstract Data sets of publication meta data with manually disambiguated author names play an important role in current author name disambiguation (AND) research. We review the most important data sets used so far, and compare their respective advantages and shortcomings. From the results of this review, we derive a set of general requirements to future AND data sets. These include both trivial requirements, like absence of errors and preservation of author order, and more substantial ones, like full disambiguation and adequate representation of publications with a small number of authors and highly variable author names. On the basis of these requirements, we create and make publicly available a new AND data set, SCAD-zbMATH. Both the quantitative analysis of this data set and the results of our initial AND experiments with a naive baseline algorithm show the SCAD-zbMATH data set to be considerably different from existing ones. We consider it a useful new resource that will challenge the state of the art in AND and benefit the AND research community.
Erfasst von	OLC
Update	2023/2/05