An Ontology Alignment Approach Combining Word Embedding and the Radius Measure

Molka Tounsi Dhouib 1 Catherine Faron Zucker 1 Andrea G. B. Tettamanzi 1
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : Ontology alignment plays a key role in achieving interoper-ability on the semantic Web. Inspired by the success of word embedding techniques in several NLP tasks, we propose a new ontology alignment approach based on the combination of word embedding and the radius measure. We tested our system on the OAEI (http://oaei. ontologymatching.org/) conference track and then applied it to aligning ontologies in a real-world case study. The experimental results show that using word embedding and the radius measure make it possible to determine, with good accuracy, not only equivalence relations, but also hierarchical relations between concepts.
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https://hal.inria.fr/hal-02348004
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Submitted on : Tuesday, November 5, 2019 - 12:13:09 PM
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Molka Tounsi Dhouib, Catherine Faron Zucker, Andrea G. B. Tettamanzi. An Ontology Alignment Approach Combining Word Embedding and the Radius Measure. SEMANTiCS 2019, Sep 2019, Karlsruhe, Germany. pp.191-197, ⟨10.1007/978-3-030-33220-4_14⟩. ⟨hal-02348004⟩

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