Abstract
Various methods using different measures have been proposed for ontology alignment. Therefore, it is necessary to evaluate the effectiveness of such measures to select better ones for more quality alignment. Current approaches for comparing these measures, are highly dependent on alignment frameworks, which may cause unreal results. In this paper, we propose a framework independent evaluation method, and discuss results of applying it to famous existing string measures.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Bouquet, P., Ehrig, M., et al.: Specification of a Common Framework for Characterizing Alignment. Technical Report deliverable 2.2.1, Knowledge Web (Statistical Research Division, Room 3000-4, Bureau of the Census, Washington, DC, 20233-9100 USA)
Levenshtein, V.: Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Soviet Physics-Doklady 10, 707–710 (1966)
Needleman, S., Wunsch, C.: A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of two Proteins. Molecular Biology 48, 443–458 (1970)
Smith, T., Waterman, M.: Identification of Common Molecular Subsequences. Molecular Biology 147, 195–197 (1981)
Monge, A.E., Elkan, C.P.: The Field-Matching Problem: Algorithm and Applications. In: Proceedings of the second international Conference on Knowledge Discovery and Data Mining (1996)
Stoilos, G., Stamou, G., et al.: A String Metric for Ontology Alignment. In: Proceedings of the ninth IEEE International Symposium on Wearable Computers, pp. 237–624 (2005)
Jaro, M.: Probabilistic Linkage of Large Public Health Data Files. Molecular Biology 14, 491–498 (1995)
Winkler, W.E.: The State Record Linkage and Current Research Problems. Technical Report RR99/04, U. S. Bureau of the Census, Statistical Research Division, Room 3000-4, Bureau of the Census, Washington, DC, 20233-9100 USA (1999)
Euzenat, J., Bach, T.L., et al.: State of the Art on Ontology Alignment. Technical Report deliverable 2.2.3, Knowledge Web (Statistical Research Division, Room 3000-4, Bureau of the Census, Washington, DC, 20233-9100 USA)
Euzenat, J., Ehrig, M., et al.: Benchmarking Methodology for Alignment Techniques. Technical Report deliverable 2.2.2, Knowledge Web (Statistical Research Division, Room 3000-4, Bureau of the Census, Washington, DC, 20233-9100 USA)
Do, H., Melnik, S., et al.: Comparison of Schema Matching Evaluations. In: Proceedings of the 2nd Int. Workshop on Web Databases (German Informatics Society)
Euzenat, J.: Towards Composing and Benchmarking Ontology Alignments. In: Proceedings of the ISWC-2003 workshop on semantic information integration, pp. 165–166 (2003)
Rahm, E., Bernstein, P.A.: A Survey of Approaches to Automatic Schema Matching. The Very Large Databases Journal 10(4), 334–350 (2001)
Sure, Y., Corcho, O., et al. (eds.): Proceedings of the 3rd Evaluation of Ontologybased tools, EON 2004 (2004)
Larose, D.T.: Discovering Knowledge In Data. John Wiley and Sons, New Jersey, USA (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hariri, B.B., Abolhassani, H. (2006). A New Evaluation Method for Ontology Alignment Measures. In: Mizoguchi, R., Shi, Z., Giunchiglia, F. (eds) The Semantic Web – ASWC 2006. ASWC 2006. Lecture Notes in Computer Science, vol 4185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11836025_25
Download citation
DOI: https://doi.org/10.1007/11836025_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38329-1
Online ISBN: 978-3-540-38331-4
eBook Packages: Computer ScienceComputer Science (R0)