SERIMI - Resource Description Similarity, RDF Instance Matching and Interlinking
Abstract
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.
Cite
@article{arxiv.1107.1104,
title = {SERIMI - Resource Description Similarity, RDF Instance Matching and Interlinking},
author = {Samur Araujo and Jan Hidders and Daniel Schwabe and Arjen P. de Vries},
journal= {arXiv preprint arXiv:1107.1104},
year = {2011}
}