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Title: The properties of property alignment on the semantic web

Authors: Michelle Cheatham; Catia Pesquita; Daniela Oliveira; Helena B. McCurdy

Addresses: Computer Science and Engineering, Wright State University, Dayton OH, USA ' Informatics, University of Lisbon, Lisbon, Portugal ' Insight Centre for Data Analytics, National University of Ireland, Galway, Ireland ' Computer Science and Engineering, Wright State University, Dayton OH, USA

Abstract: The performance of alignment systems on property matching lags behind that on class and instance matching. This work seeks to understand the reasons for this and consider avenues for improvement. The paper contains an exploration of the performance of current alignment systems on the only commonly accepted alignment benchmark that involves matches between properties. A second benchmark involving properties from DBPedia and YAGO, scaled to be within the capabilities of most existing alignment systems, is also proposed. A basic approach focused on aligning properties is then presented and evaluated using both benchmarks to serve as a baseline against which to compare more complex matchers on the property alignment task. The results show that even a relatively simplistic approach can achieve a significantly higher F-measure than current matchers. Finally, an existing full-featured alignment system is augmented with the basic property matching approach and the difference in performance is assessed.

Keywords: ontology alignment; semantic data integration; ontology alignment benchmark; property alignment; relation alignment; semantic similarity metric; lexical similarity metric; PropString; semantic web; ontology.

DOI: 10.1504/IJMSO.2018.096452

International Journal of Metadata, Semantics and Ontologies, 2018 Vol.13 No.1, pp.42 - 56

Received: 08 Aug 2017
Accepted: 28 Jul 2018

Published online: 30 Nov 2018 *

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