Alignment-Based Partitioning of Large-Scale Ontologies

  • Fayçal Hamdi
  • Brigitte Safar
  • Chantal Reynaud
  • Haïfa Zargayouna
Part of the Studies in Computational Intelligence book series (SCI, volume 292)


Ontology alignment is an important task for information integration systems that can make different resources, described by various and heterogeneous ontologies, interoperate. However very large ontologies have been built in some domains such as medicine or agronomy and the challenge now lays in scaling up alignment techniques that often perform complex tasks. In this paper, we propose two partitioning methods which have been designed to take the alignment objective into account in the partitioning process as soon as possible. These methods transform the two ontologies to be aligned into two sets of blocks of a limited size. Furthermore, the elements of the two ontologies that might be aligned are grouped in a minimal set of blocks and the comparison is then enacted upon these blocks. Results of experiments performed by the two methods on various pairs of ontologies are promising.


Ontology Matching Ontology Partitioning 


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  1. Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. The Scientific American, 34–43 (2001)Google Scholar
  2. Grau, B.C., Parsia, B., Sirin, E., Kalyanpur, A.: Automatic Partitioning of OWL Ontologies Using e-connections. In: DL 2005, Proceedings of the 18th International Workshop on Description Logics (2005)Google Scholar
  3. Guha, S., Rastogi, R., Shim, K.: ROCK: A Robust Clustering Algorithm for Categorical Attributes. Information Systems 25(5), 345–366 (2000)CrossRefGoogle Scholar
  4. Haase, P., Honavar, V., Kutz, O., Sure, Y., Tamilin, A. (eds.): Proceedings of the 1st International Workshop on Modular Ontologies, WoMO 2006, co-located with the International Semantic Web Conference, ISWC 2006. CEUR Workshop Proceedings, vol. 232 (2007),
  5. Hamdi, F., Zargayouna, H., Safar, B., Reynaud, C.: TaxoMap in the OAEI 2008 Alignment Contest. In: Proceedings of the 3th International Workshop on Ontology Matching, OM 2008 (2008)Google Scholar
  6. Hu, W., Qu, Y., Cheng, G.: Matching large ontologies: A divide-and-conquer approach. Data Knowl. Eng. 67(1), 140–160 (2008)CrossRefGoogle Scholar
  7. Hu, W., Zhao, Y., Qu, Y.: Partition-Based Block Matching of Large Class Hierarchies. In: Mizoguchi, R., Shi, Z.-Z., Giunchiglia, F. (eds.) ASWC 2006. LNCS, vol. 4185, pp. 72–83. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. Nagy, M., Vargas-Vera, M., Stolarski, P., Motta, E.: DSSim Results for OAEI. In: Proceedings of the 3th International Workshop on Ontology Matching, OM 2008 (2008)Google Scholar
  9. Noy, N.F., Musen, M.A.: PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. In: AAAI/IAAI, pp. 450–455 (2000)Google Scholar
  10. Shvaiko, P., Euzenat, J.: A Survey of Schema-Based Matching Approaches. Journal on Data Semantics IV, 146–171Google Scholar
  11. Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB Journal: Very Large Data Bases 10(4), 334–350 (2001)zbMATHCrossRefGoogle Scholar
  12. Reynaud, C., Safar, B.: Techniques structurelles d’alignement pour portails web. RNTI, Revue des Nouvelles Technologies de l’Information (2007)Google Scholar
  13. Stuckenschmidt, H., Klein, M.: Structured-Based Partitioning of Large Concept Hierarchies. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 289–303. Springer, Heidelberg (2004)Google Scholar
  14. Wang, P., Xu, B.: Lily: Ontology Alignment Results for OAEI 2008. In: Proceedings of the 3th International Workshop on Ontology Matching, OM 2008 (2008)Google Scholar
  15. Wang, Z., Wang, Y., Zhang, S., Shen, G., Du, T.: Matching Large Scale Ontology Effectively. In: Mizoguchi, R., Shi, Z.-Z., Giunchiglia, F. (eds.) ASWC 2006. LNCS, vol. 4185, pp. 99–105. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  16. Wu, Z., Palmer, M.: Verb semantics and lexical selection. In: Proc. 32nd Annual Meeting of the Association for Computational Linguistics (ACL), pp. 133–138 (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Fayçal Hamdi
    • 1
  • Brigitte Safar
    • 1
  • Chantal Reynaud
    • 1
  • Haïfa Zargayouna
    • 2
  1. 1.LRI, Université Paris-Sud 11 - CNRS UMR 8623, Bât. G, INRIA Saclay - Île-de-FranceOrsayFrance
  2. 2.LIPNUniversité Paris 13 - CNRS UMR 7030VilletaneuseFrance

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