There is an increasing interest in publishing data using the
Linked Open Data philosophy. To link the RDF datasets,
a link discovery task is performed to generate owl:sameAs
links. There are two ways to perform this task: by means
of a classi er or a link speci cation; we focus in the latter
approach. Current link speci cation techniques only use
the data properties of the instances that they are linking,
and they do not take the context information into account.
In this paper, we present a proposal that aims to generate
context-aware link speci cations to improve the regular
link speci cations, increasing the e ectiveness of the results
in several real-world scenarios where the context is crucial.
Our context-aware link speci cations are independent from
similarity functions, transformations or aggregations. We
have evaluated our proposal using two real-world scenarios
in which we improve precision and recall with respect to
regular link speci cations in 23% and 58%, respectively.Ministerio de Economía y Competitividad TIN2013-40848-
