Abstract
Many algorithms dealing with thematching task have been proposed in the past, most of them not considering instances. Only a few existing systems like [EM07] or [DMDH04] use the information provided by instances in their matching algorithms. Due to the fact that ontologies offer the possibility to model instances within the ontology, these should definitely be used to increase the accuracy of the matching results. Additionally, the set of instances probably provides more information about the meaning of a concept than its label. Thus, we propose a new instance-based ontology matcher which should extend existing libraries to enhance the matching quality.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Doan, A., Madhavan, J., Domingos, P., Halevy, A.Y.: Ontology Matching: A Machine Learning Approach. In: Handbook on Ontologies, pp. 385–404. Springer, Heidelberg (2004)
Engmann, D., Maßmann, S.: Instance Matching with COMA++. In: Datenbanksysteme in Business, Technologie und Web (BTW 2007), Workshop Proceedings, Aachen, Germany, März 5-6 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zaiß, K., Schlüter, T., Conrad, S. (2008). Instance-Based Ontology Matching Using Regular Expressions. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2008 Workshops. OTM 2008. Lecture Notes in Computer Science, vol 5333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88875-8_19
Download citation
DOI: https://doi.org/10.1007/978-3-540-88875-8_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88874-1
Online ISBN: 978-3-540-88875-8
eBook Packages: Computer ScienceComputer Science (R0)