  In this article we propose a holistic approach to discover relations in art
historical communities and enrich historians' biographies and archival
descriptions with graph patterns relevant to art historiographic enquiry. We
use exploratory data analysis to detect patterns, we select features, and we
use them to evaluate classification models to predict new relations, to be
recommended to archivists during the cataloguing phase. Results show that
relations based on biographical information can be addressed with higher
precision than relations based on research topics or institutional relations.
Deterministic and a priori rules present better results than probabilistic
methods.
