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arXiv 2003.05370cs.AI
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Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules

City, University of London(伦敦大学城市学院);University of Oslo(奥斯陆大学);Medical University of Vienna(维也纳医科大学);University of Oxford(牛津大学);Miami University(迈阿密大学)

Ernesto Jiménez-Ruiz, Asan Agibetov, Jiaoyan Chen, Matthias Samwald, Valerie Cross

英文摘要:

Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In this paper we present an approach that combines a neural embedding model and logic-based modules to accurately divide an input ontology matching task into smaller and more tractable matching (sub)tasks. We have conducted a comprehensive evaluation using the datasets of the Ontology Alignment Evaluation Initiative. The results are encouraging and suggest that the proposed method is adequate in practice and can be integrated within the workflow of systems unable to cope with very large ontologies.

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