Abstract
Relational databases are valuable sources for ontology learning. Previous work showed how precise ontologies can be learned and be fruitfully exploited to solve practical problems, such as ensuring integration and interoperation of heterogeneous databases. However, a major persisting limitation of the existing approaches is the derivation of ontologies with flat structure that simply mirror the schema of the source databases. In this paper, we present the RTAXON learning method that shows how the content of the databases can be exploited to identify categorization patterns from which class hierarchies can be generated. This fully formalized method combines a classical database schema analysis with hierarchy mining in the stored data. RTAXON is one of the methods implemented in RDBToOnto, a comprehensive tool that support the transitioning process from access to the data to generation of populated ontologies.
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
Abiteboul, S., Hull, R., Vianu, V. (eds.): Foundations of databases. John Benjamins, Amsterdam (1995)
Astrova, I.: Reverse Engineering of Relational Databases to Ontologies. In: Bussler, C.J., Davies, J., Fensel, D., Studer, R. (eds.) ESWS 2004. LNCS, vol. 3053, pp. 327–341. Springer, Heidelberg (2004)
Astrova, I., Stantic, B.: Reverse Engineering of Relational Databases to Ontologies: An Approach Based on an Analysis of HTML Forms. In: Workshop on Knowledge Discovery and Ontologies (KDO) at ECML/PKDD 2004, Pisa (2004)
Barrasa, J., Corcho, O., Gómez-Pérez, A.: R2O, an Extensible and Semantically Based Database-to-Ontology Mapping Language. In: Second Workshop on Semantic Web and Databases (SWDB 2004), Toronto, Canada (2004)
Behm, A., Geppert, A., Dittrich, K.R.: On the Migration of Relational Schemas and Data to Object-Oriented Database Systems. In: Györkös, J., Krisper, M., Mayr, H.C. (eds.) Proc. 5th International Conference on Re-Technologies for Information Systems, Oesterreichische Computer Gesellschaft, Klagenfurt, Austria, pp. 13–33 (1997), http://citeseer.ist.psu.edu/behm97migration.html
Benslimane, S.M., Benslimane, D., Malki, M., Maamar, Z., Thiran, P., Amghar, Y., Hacid, M.-S.: Ontology development for the Semantic Web: An HTML form-based reverse engineering approach. International Journal of Web Engineering 6(2), 143–164 (2007)
Bizer, C.: D2R MAP - A Database to RDF Mapping Language. In: Proceedings of WWW 2003, Budapest (2003)
Cerbah, F.: Learning highly structured semantic repositories from relational databases – The RDBToOnto tool. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 777–781. Springer, Heidelberg (2008)
de Laborda, C.P., Conrad, S.: Relational.OWL: a data and schema representation format based on OWL. In: APCCM 2005: Proceedings of the 2nd Asia-Pacific conference on Conceptual modelling, pp. 89–96. Australian Computer Society, Inc., Darlinghurst (2005)
Lammari, N., Comyn-Wattiau, I., Akoka, J.: Extracting Generalization Hierarchies from Relational Databases. A Reverse Engineering Approach. Data and Knowledge Engineering 63, 568–589 (2007)
Li, M., Du, X., Wang, S.: Learning ontology from relational database. In: Proceedings of 2005 International Conference on Machine Learning and Cybernetics, vol. 6, pp. 3410–3415. IEEE, Los Alamitos (2005)
Premerlani, W., Blaha, M.: An approach for reverse engineering of relational databases. Communications of the ACM 37(5) (1994)
Ramanathan, S., Hodges, J.: Extraction of object-oriented structures from existing relational databases. ACM SIGMOD 26(1) (1997)
Stojanovic, L., Stojanovic, N., Volz, R.: Migrating data-intensive Web Sites into the Semantic Web. In: Proceedings of the ACM Symposium on Applied Computing (SAC 2002), Madrid (2002)
Tari, Z., Bukhres, O.A., Stokes, J., Hammoudi, S.: The Reengineering of Relational Databases Based on Key and Data Correlations. In: DS-7, p. 184 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Cerbah, F. (2010). Learning Ontologies with Deep Class Hierarchies by Mining the Content of Relational Databases. In: Guillet, F., Ritschard, G., Zighed, D.A., Briand, H. (eds) Advances in Knowledge Discovery and Management. Studies in Computational Intelligence, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00580-0_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-00580-0_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00579-4
Online ISBN: 978-3-642-00580-0
eBook Packages: EngineeringEngineering (R0)