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arXiv · 2204.04040

Ontology Matching Through Absolute Orientation of Embedding Spaces

Jan Portisch·Guilherme Costa·Karolin Stefani·Katharina Kreplin·Michael Hladik·Heiko Paulheim
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Abstract

Ontology matching is a core task when creating interoperable and linked open datasets. In this paper, we explore a novel structure-based mapping approach which is based on knowledge graph embeddings: The ontologies to be matched are embedded, and an approach known as absolute orientation is used to align the two embedding spaces. Next to the approach, the paper presents a first, preliminary evaluation using synthetic and real-world datasets. We find in experiments with synthetic data, that the approach works very well on similarly structured graphs; it handles alignment noise better than size and structural differences in the ontologies.

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Jan Portisch, Guilherme Costa, Karolin Stefani, Katharina Kreplin, Michael Hladik, Heiko Paulheim. 2022-04-08. Ontology Matching Through Absolute Orientation of Embedding Spaces. https://arxiv.org/abs/2204.04040

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