We view match as an operator that takes two graph-like structures (e.g., XML schemas) and produces a mapping between the nodes of these graphs that correspond semantically to each other. Semantic schema matching is based on the two ideas: (i) we discover mappings by computing semantic relations (e.g., equivalence, more general); (ii) we determine semantic relations by analyzing the meaning (concepts, not labels) which is codified in the elements and the structures of schemas. In this paper we present basic and optimized algorithms for semantic schema matching, and we discuss their implementation within the S-Match system. We also validate the approach and evaluate S-Match against three state of the art matching systems. The results look promising, in particular for what concerns quality and performance.


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  1. 1.
    Avesani, P., Giunchiglia, F., Yatskevich, M.: A large scale taxonomy mapping evaluation. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 67–81. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Bergamaschi, S., Castano, S., Vincini, M.: Semantic integration of semistructured and structured data sources. SIGMOD Record, 54–59 (1999)Google Scholar
  3. 3.
    Bernstein, P., Melnik, S., Petropoulos, M., Quix, C.: Industrial-strength schema matching. SIGMOD Record 33(4), 38–43 (2004)CrossRefGoogle Scholar
  4. 4.
    Le Berre, D.: A satisfiability library for Java, http://www.sat4j.org/
  5. 5.
    Bouquet, P., Serafini, L., Zanobini, S.: Semantic coordination: A new approach and an application. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 130–145. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  6. 6.
    Davis, M., Longemann, G., Loveland, D.: A machine program for theorem proving. Journal of the ACM 5(7), 394–397 (1962)MATHCrossRefGoogle Scholar
  7. 7.
    Dhamankar, R., Lee, Y., Doan, A., Halevy, A., Domingos, P.: iMAP: Discovering complex semantic matches between database schemas. In: Proceedings of SIGMOD, pp. 383–394 (2004)Google Scholar
  8. 8.
    Do, H.H., Rahm, E.: COMA - a system for flexible combination of schema matching approaches. In: Proceedings of VLDB, pp. 610–621 (2002)Google Scholar
  9. 9.
    Euzenat, J., Valtchev, P.: Similarity-based ontology alignment in OWL-lite. In: Proceedings of ECAI, pp. 333–337 (2004)Google Scholar
  10. 10.
    Gal, A., Anaby-Tavor, A., Trombetta, A., Montesi, D.: A framework for modeling and evaluating automatic semantic reconciliation. VLDB Journal 14(1) (2005)Google Scholar
  11. 11.
    Giunchiglia, F., Shvaiko, P.: Semantic matching. KER Journal 18(3) (2003)Google Scholar
  12. 12.
    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)CrossRefGoogle Scholar
  13. 13.
    Giunchiglia, F., Yatskevich, M., Giunchiglia, E.: Efficient semantic matching. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 272–289. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  14. 14.
    Guarino, N.: The role of ontologies for the Semantic Web (and beyond). Technical report, Laboratory for Applied Ontology, ISTC-CNR (2004)Google Scholar
  15. 15.
    Haarslev, V., Moller, R., Wessel, M.: RACER: Semantic middleware for industrial projects based on RDF/OWL, a W3C Standard, http://www.sts.tu-harburg.de/~r.f.moeller/racer/
  16. 16.
    Kang, J., Naughton, J.F.: On schema matching with opaque column names and data values. In: Proceedings of SIGMOD, pp. 205–216 (2003)Google Scholar
  17. 17.
    Madhavan, J., Bernstein, P., Rahm, E.: Generic schema matching with Cupid. In: Proceedings of VLDB, pp. 49–58 (2001)Google Scholar
  18. 18.
    Magnini, B., Serafini, L., Speranza, M.: Making explicit the semantics hidden in schema models. In: Proceedings of workshop on HLTSWWS at ISWC (2003)Google Scholar
  19. 19.
    Melnik, S., Garcia-Molina, H., Rahm, E.: Similarity flooding: A versatile graph matching algorithm. In: Proceedings of ICDE, pp. 117–128 (2002)Google Scholar
  20. 20.
    Melnik, S., Rahm, E., Bernstein, P.: Rondo: A programming platform for generic model management. In: Proceedings of SIGMOD, pp. 193–204 (2003)Google Scholar
  21. 21.
    Miller, A.G.: WordNet: A lexical database for English. Communications of the ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
  22. 22.
    Pan, J.Z.: Description Logics: reasoning support for the Semantic Web. PhD thesis, School of Computer Science, The University of Manchester (2004)Google Scholar
  23. 23.
    Plaisted, D., Greenbaum, S.: A structure-preserving clause form translation. Journal of Symbolic Computation 2, 293–304 (1986)MATHCrossRefMathSciNetGoogle Scholar
  24. 24.
    Rahm, E., Bernstein, P.: A survey of approaches to automatic schema matching. VLDB Journal 10(4), 334–350 (2001)MATHCrossRefGoogle Scholar
  25. 25.
    Shvaiko, P., Euzenat, J.: A survey of schema-based matching approaches. Journal on Data Semantics IV (2005)Google Scholar
  26. 26.
    Smith, M.K., Welty, C., McGuinness, D.L.: OWL web ontology language guide. Technical report, World Wide Web Consortium (W3C) (February 10, 2004), http://www.w3.org/TR/2004/REC-owl-guide-20040210/

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Fausto Giunchiglia
    • 1
  • Pavel Shvaiko
    • 1
  • Mikalai Yatskevich
    • 1
  1. 1.University of TrentoPovo, TrentoItaly

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