  The interlinking of datasets published in the Linked Data Cloud is a
challenging problem and a key factor for the success of the Semantic Web.
Manual rule-based methods are the most effective solution for the problem, but
they require skilled human data publishers going through a laborious, error
prone and time-consuming process for manually describing rules mapping
instances between two datasets. Thus, an automatic approach for solving this
problem is more than welcome. In this paper, we propose a novel interlinking
method, SERIMI, for solving this problem automatically. SERIMI matches
instances between a source and a target datasets, without prior knowledge of
the data, domain or schema of these datasets. Experiments conducted with
benchmark collections demonstrate that our approach considerably outperforms
state-of-the-art automatic approaches for solving the interlinking problem on
the Linked Data Cloud.
