Abstract
(Semi-)automatic mapping – also called (semi-)automatic alignment – of ontologies is a core task to achieve interoperability when two agents or services use different ontologies. In the existing literature, the focus has so far been on improving the quality of mapping results. We here consider QOM, Quick Ontology Mapping, as a way to trade off between effectiveness (i.e. quality) and efficiency of the mapping generation algorithms. We show that QOM has lower run-time complexity than existing prominent approaches. Then, we show in experiments that this theoretical investigation translates into practical benefits. While QOM gives up some of the possibilities for producing high-quality results in favor of efficiency, our experiments show that this loss of quality is marginal.
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
Preview
Unable to display preview. Download preview PDF.
References
Agrawal, R., Srikant, R.: On integrating catalogs. In: Proceedings of the tenth international conference on World Wide Web, pp. 603–612 (2001)
Noy, N.F., Musen, M.A.: The PROMPT suite: interactive tools for ontology merging and mapping. International Journal of Human-Computer Studies 59, 983–1024 (2003)
Doan, A., Domingos, P., Halevy, A.: Learning to match the schemas of data sources: A multistrategy approach. VLDB Journal 50, 279–301 (2003)
Ehrig, M., Haase, P., van Harmelen, F., Siebes, R., Staab, S., Stuckenschmidt, H., Studer, R., Tempich, C.: The SWAP data and metadata model for semantics-based peer-to-peer systems. In: Schillo, M., Klusch, M., Müller, J., Tianfield, H. (eds.) MATES 2003. LNCS (LNAI), vol. 2831, pp. 144–155. Springer, Heidelberg (2003)
Hotho, A., Staab, S., Stumme, G.: Ontologies improve text document clustering. In: Proceedings of the International Conference on Data Mining—ICDM 2003, IEEE Press, Los Alamitos (2003)
Ehrig, M., Staab, S.: Quick ontology mapping with QOM. Technical report, University of Karlsruhe, Institute AIFB (2004), http://www.aifb.uni-karlsruhe.de/WBS/meh/mapping/
Do, H., Rahm, E.: COMA- a system for flexible combination of schema matching approaches. In: Proceedings of the 28th VLDB Conference, Hong Kong, China (2002)
Dhamankar, R., Lee, Y., Doan, A., Halevy, A., Domingos, P.: imap: discovering complex semantic matches between database schemas. In: Proceedings of the 2004 ACM SIGMOD international conference on Management of data, pp. 383–394 (2004)
Ehrig, M., Sure, Y.: Ontology mapping - an integrated approach. In: Bussler, C.J., Davies, J., Fensel, D., Studer, R. (eds.) ESWS 2004. LNCS, vol. 3053, pp. 76–91. Springer, Heidelberg (2004)
Euzenat, J., Valtchev, P.: An integrative proximity measure for ontology alignment. In: Doan, A., Halevy, A., Noy, N. (eds.) Proceedings of the Semantic IntegrationWorkshop at ISWC 2003 (2003)
Bisson, G.: Why and how to define a similarity measure for object based representation systems. Towards Very Large Knowledge Bases, 236–246 (1995)
Maedche, A., Staab, S.: Measuring similarity between ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, p. 251. Springer, Heidelberg (2002)
Levenshtein, I.V.: Binary codes capable of correcting deletions, insertions, and reversals. Cybernetics and Control Theory (1966)
Cox, T., Cox, M.: Multidimensional Scaling. Chapman and Hall, Boca Raton (1994)
Boddy, M.: Anytime problem solving using dynamic programming. In: Proceedings of the Ninth National Conference on Artificial Intelligence, Anaheim, California, pp. 738–743. Shaker Verlag (1991)
Tempich, C., Volz, R.: Towards a benchmark for semantic web reasoners - an analysis of the DAML ontology library. In: Sure, Y. (ed.) Evaluation of Ontology-based Tools (EON 2003) at Second International SemanticWeb Conference (ISWC 2003) (2003)
Do, H., Melnik, S., Rahm, E.: Comparison of schema matching evaluations. In: Proceedings of the second int. workshop onWeb Databases (German Informatics Society) (2002)
Rodríguez, M.A., Egenhofer, M.J.: Determining semantic similarity among entity classes from different ontologies. IEEE Transactions on Knowledge and Data Engineering (2000)
Mitra, P., Wiederhold, G., Kersten, M.: A graph-oriented model for articulation of ontology interdependencies. In: Zaniolo, C., Grust, T., Scholl, M.H., Lockemann, P.C. (eds.) EDBT 2000. LNCS, vol. 1777, p. 86. Springer, Heidelberg (2000)
Bouquet, P., Magnini, B., Serafini, L., Zanobini, S.: A SAT-based algorithm for context matching. In: IV International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT 2003), Stanford University, CA, USA (2003)
McCallum, A., Nigam, K., Ungar, L.H.: Efficient clustering of high-dimensional data sets with application to reference matching. In: Knowledge Discovery and Data Mining, pp. 169–178 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ehrig, M., Staab, S. (2004). QOM – Quick Ontology Mapping. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds) The Semantic Web – ISWC 2004. ISWC 2004. Lecture Notes in Computer Science, vol 3298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30475-3_47
Download citation
DOI: https://doi.org/10.1007/978-3-540-30475-3_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23798-3
Online ISBN: 978-3-540-30475-3
eBook Packages: Springer Book Archive