Homonym Detection in Curated Bibliographies: Learning from dblp's Experience

Marcel R. Ackermann, Florian Reitz

Abstract: Identifying (and fixing) homonymous and synonymous author profiles is one of the major tasks of curating personalized bibliographic metadata repositories like the dblp computer science bibliography. In this paper, we present a machine learning approach to identify homonymous profiles. We train our model on a novel gold-standard data set derived from the past years of active, manual curation at dblp.