SERIMI - Resource Description Similarity, RDF Instance Matching and Interlinking

TL;DR

SERIMI is an automatic method for linking RDF instances across datasets in the Linked Data Cloud, eliminating the need for manual rule creation and outperforming existing approaches.

Contribution

It introduces a novel automatic interlinking technique that requires no prior knowledge of data, domain, or schema, improving accuracy over state-of-the-art methods.

Findings

SERIMI outperforms existing automatic interlinking approaches.

The method works without prior knowledge of datasets.

Experiments on benchmark collections validate its effectiveness.

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.