Abstract
In this paper, we investigate a principled approach for defining and discovering probabilistic mappings between two taxonomies. First, we compare two ways of modeling probabilistic mappings which are compatible with the logical constraints declared in each taxonomy. Then we describe a generate and test algorithm which minimizes the number of calls to the probability estimator for determining those mappings whose probability exceeds a certain threshold. Finally, we provide an experimental analysis of this approach.
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.
Similar content being viewed by others
References
Aumueller, D., Do, H.H., Massmann, S., Rahm, E.: Schema and ontology matching with COMA++. In: SIGMOD 2005, ACM, New York (2005)
Benjelloun, O., Sarma, A.D., Halevy, A.Y., Widom, J.: ULDBs: Databases with uncertainty and lineage. In: VLDB (2006)
Castano, S., Ferrara, A., Lorusso, D., Näth, T.H., Möller, R.: Mapping validation by probabilistic reasoning. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 170–184. Springer, Heidelberg (2008)
Castano, S., Ferrara, A., Montanelli, S.: H-MATCH: an algorithm for dynamically matching ontologies in peer-based systems. In: SWDB (2003)
Chiticariu, L., Hernández, M.A., Kolaitis, P.G., Popa, L.: Semi-automatic schema integration in clio. In: VLDB (2007)
Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 2nd edn. The MIT Press, Cambridge (2001)
Dalvi, N.N., Suciu, D.: Answering queries from statistics and probabilistic views. In: VLDB (2005)
Dean, M., Schreiber, G.: OWL web ontology language reference. W3C recommendation, W3C (2004)
Degroot, M.H.: Optimal Statistical Decision. Wiley Classics Library (2004)
Do, H., Rahm, E.: COMA - a system for flexible combination of schema matching approaches. In: VLDB (2002)
Doan, A., Domingos, P., Levy, A.Y.: Learning mappings between data schemas. In: Proceedings of the AAAI 2000 Workshop on Learning Statistical Models from Relational Data (2000)
Doan, A., Madhavan, J., Domingos, P., Halevy, A.Y.: Learning to map between ontologies on the semantic web. In: WWW (2002)
Dong, X.L., Halevy, A.Y., Yu, C.: Data integration with uncertainty. VLDB Journal (2007)
Euzenat, J., Shvaiko, P.: Ontology matching. Springer, Heidelberg (2007)
Euzenat, J., Valtchev, P.: Similarity-based ontology alignment in OWL-lite. In: ECAI (2004)
Flake, G.W., Lawrence, S.: Efficient SVM regression training with SMO. Machine Learning (2002)
Giunchiglia, F., Shvaiko, P., Yatskevich, M.: S-Match: an algorithm and an implementation of semantic matching. In: Bussler, C.J., Davies, J., Fensel, D., Studer, R. (eds.) ESWS 2004. LNCS, vol. 3053, pp. 61–75. Springer, Heidelberg (2004)
Hamdi, F., Zargayouna, H., Safar, B., Reynaud, C.: TaxoMap in the OAEI 2008 alignment contest. In: OAEI 2008 Campaign - Int. Workshop on Ontology Matching (2008)
Hayes, P. (ed.): RDF Semantics. World Wide Web Consortium (2004)
Ichise, R., Takeda, H., Honiden, S.: Integrating multiple internet directories by instance-based learning. In: IJCAI, vol. 18 (2003)
Ichise, R., Hamasaki, M., Takeda, H.: Discovering relationships among catalogs. In: Suzuki, E., Arikawa, S. (eds.) DS 2004. LNCS (LNAI), vol. 3245. Springer, Heidelberg (2004)
Li, W.S., Clifton, C.: Semint: a tool for identifying attribute correspondences in heterogeneous databases using neural networks. Data Knowl. Eng. 33(1) (2000)
Madhavan, J., Bernstein, P.A., Doan, A., Halevy, A.: Corpus-based schema matching. In: International Conference on Data Engineering (2005)
Madhavan, J., Bernstein, P.A., Rahm, E.: Generic schema matching with cupid. VLDB Journal (2001)
Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB Journal (2001)
Stumme, G., Maedche, A.: FCA-MERGE: Bottom-Up Merging of Ontologies. In: Proc. of the 17th International Joint Conference on Artificial Intelligence (2001)
Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tournaire, R., Petit, JM., Rousset, MC., Termier, A. (2010). Combining Logic and Probabilities for Discovering Mappings between Taxonomies. In: Bi, Y., Williams, MA. (eds) Knowledge Science, Engineering and Management. KSEM 2010. Lecture Notes in Computer Science(), vol 6291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15280-1_48
Download citation
DOI: https://doi.org/10.1007/978-3-642-15280-1_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15279-5
Online ISBN: 978-3-642-15280-1
eBook Packages: Computer ScienceComputer Science (R0)