A link key is based on a set of property pairs and can be used to identify pairs of individuals representing the same real-world entity in two different RDF datasets. Various algorithms are aimed at discovering link keys which usually output a large number of candidates, making link key selection and validation a challenging task. In this paper, we propose an approach combining Formal Concept Analysis (FCA) for discovering link key candidates and building a link key lattice, and then hierarchical clustering over a given set of candidates for building a representative set of link keys.
Such a link key set should minimize the number of candidates to be validated while preserving a maximal number of links between individuals. The paper also provides a series of experiments which are performed over different RDF datasets, showing the effectiveness of the approach and the ability of hierarchical clustering to return a concise and meaningful set of candidates while preserving the ordinal structure of the link key lattice.