Formalizing the XML Schema Matching Problem as a Constraint Optimization Problem

  • Marko Smiljanić
  • Maurice van Keulen
  • Willem Jonker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3588)

Abstract

The first step in finding an efficient way to solve any difficult problem is making a complete, possibly formal, problem specification. This paper introduces a formal specification for the problem of semantic XML schema matching. Semantic schema matching has been extensively researched, and many matching systems have been developed. However, formal specifications of problems being solved by these systems do not exist, or are partial. In this paper, we analyze the problem of semantic schema matching, identify its main components and deliver a formal specification based on the constraint optimization problem formalism. Throughout the paper, we consider the schema matching problem as encountered in the context of a large scale XML schema matching application.

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References

  1. 1.
    Bartak, R.: Constraint programming: In pursuit of the holy grail. In: Proceedings of the Week of Doctoral Students (WDS), June 1999, pp. 555–564 (1999)Google Scholar
  2. 2.
    Bergholz, A., Freytag, J.C.: Querying Semistructured Data Based on Schema Matching. In: Connor, R.C.H., Mendelzon, A.O. (eds.) DBPL 1999. LNCS, vol. 1949, p. 168. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  3. 3.
    Bernstein, P.A., Melnik, S., Petropoulos, M., Quix, C.: Industrial-strength schema matching. SIGMOD Rec. 33(4), 38–43 (2004)CrossRefGoogle Scholar
  4. 4.
    Do, H., Melnik, S., Rahm, E.: Comparison of schema matching evaluations. In: Proceedings of the 2nd Int. Workshop on Web Databases (2002)Google Scholar
  5. 5.
    Do, H.H., Rahm, E.: COMA — A system for flexible combination of schema matching approaches. In: Bernstein, P.A., et al. (eds.) Proc. Intl. Conf VLDB 2002. Morgan Kaufmann Publishers, San Francisco (2002)Google Scholar
  6. 6.
    Doan, A.: Learning to Map between Structured Representations of Data. PhD thesis, University of Washington (2002)Google Scholar
  7. 7.
    He, B., Chang, K.C.-C.: A holistic paradigm for large scale schema matching. SIGMOD Rec. 33(4), 20–25 (2004)CrossRefGoogle Scholar
  8. 8.
    Madhavan, J., Bernstein, P.A., Domingos, P., Halevy, A.Y.: Representing and reasoning about mappings between domain models. In: Proc. Conf (AAAI/IAAI 2002), pp. 80–86 (2002)Google Scholar
  9. 9.
    Madhavan, J., Bernstein, P.A., Rahm, E.: Generic schema matching with cupid. In: Proceedings of the 27th International Conference on Very Large Data Bases(VLDB 2001), Orlando, September 2001, pp. 49–58. Morgan Kaufmann, San Francisco (2001)Google Scholar
  10. 10.
    Marriott, K., Stuckey, P.J.: Programming with Constraints: an Introduction. MIT Press, Cambridge (1998)MATHGoogle Scholar
  11. 11.
    Michalewicz, Z., Fogel, D.B.: How to Solve It: Modern Heuristics, December 1999. Springer, Heidelberg (1999)Google Scholar
  12. 12.
    Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB Journal: Very Large Data Bases 10(4), 334–350 (2001)MATHCrossRefGoogle Scholar
  13. 13.
    Rahm, E., Do, H.-H., Maßmann, S.: Matching large xml schemas. SIGMOD Rec. 33(4), 26–31 (2004)CrossRefGoogle Scholar
  14. 14.
    Smiljanić, M., van Keulen, M., Jonker, W.: Defining the XML Schema Matching Problem for a Personal Schema Based Query Answering System. Technical Report TR-CTIT-04-17, Centre for Telematics and Information Technology (April 2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Marko Smiljanić
    • 1
  • Maurice van Keulen
    • 1
  • Willem Jonker
    • 1
    • 2
  1. 1.University of TwenteEnschedeThe Netherlands
  2. 2.Philips ResearchEindhovenThe Netherlands

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