Link Discovery with Guaranteed Reduction Ratio in Affine Spaces with Minkowski Measures

Abstract

Time-efficient algorithms are essential to address the complex linking tasks that arise when trying to discover links on the Web of Data. Although several lossless approaches have been developed for this exact purpose, they do not offer theoretical guarantees with respect to their performance. In this paper, we address this drawback by presenting the first Link Discovery approach with theoretical quality guarantees. In particular, we prove that given an achievable reduction ratio r, our Link Discovery approach $\mathcal{HR}^3$ can achieve a reduction ratio r′ ≤ r in a metric space where distances are measured by the means of a Minkowski metric of any order p ≥ 2. We compare $\mathcal{HR}^3$ and the HYPPO algorithm implemented in LIMES 0.5 with respect to the number of comparisons they carry out. In addition, we compare our approach with the algorithms implemented in the state-of-the-art frameworks LIMES 0.5 and SILK 2.5 with respect to runtime. We show that $\mathcal{HR}^3$ outperforms these previous approaches with respect to runtime in each of our four experimental setups.

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