  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 and
evaluate a machine learning approach to identify homonymous author
bibliographies using a simple multilayer perceptron setup. We train our model
on a novel gold-standard data set derived from the past years of active, manual
curation at the dblp computer science bibliography.
