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Semantic Matching

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Encyclopedia of Database Systems

Definition

Semantic matching: given two graph representations of ontologies G1 and G2, compute N1 × N2 mapping elements 〈ID i,j , n1 i , n2 j , R′〉 , with n1 i ∈ G1, i = 1,...,N1, n2 j ∈ G2, j = 1,...,N2 and R′ the strongest semantic relation which is supposed to hold between the concepts at nodes n1 i and n2 j .

A mapping element is a 4-tuple 〈ID ij , n1 i , n2 j , R〉, i = 1,...,N1; j = 1,...,N2; where ID ij is a unique identifier of the given mapping element; n1 i is the i-th node of the first graph, N1 is the number of nodes in the first graph; n2 j is the j-th node of the second graph, N2 is the number of nodes in the second graph; and R specifies a semantic relation which is supposed to hold between the concepts at nodes n1 i and n2 j .

The semantic relations are within equivalence (=), more general (⊒), less general (⊑), disjointness (⊥) and overlapping (⊓). When none of the above mentioned relations can be explicitly computed, the special idk(I don’t know) relation is...

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  1. Avesani P., Giunchiglia F., and Yatskevich M. A large scale taxonomy mapping evaluation. In Proc. Fourth Int. Semantic Web Conf., 2005, pp. 67–81.

    Google Scholar 

  2. Batini C., Lenzerini M., and Navathe S. A comparative analysis of methodologies for database schema integration. ACM Comput. Surv., 18(4):323–364, 1986.

    Google Scholar 

  3. Bernstein P., Melnik S., Petropoulos M., and Quix C. Industrial-strength schema matching. ACM SIGMOD Rec., 33(4):38–43, 2004.

    Google Scholar 

  4. Bouquet P., Serafini L., and Zanobini S. Semantic coordination: a new approach and an application. In Proc. Second Int. Semantic Web Conf., 2003, pp. 130–145.

    Google Scholar 

  5. Doan A., Madhavan J., Dhamankar R., Domingos P., and Halevy A.Y. Learning to match ontologies on the Semantic Web. VLDB J., 12(4):303–319, 2003.

    Google Scholar 

  6. Euzenat J. and Shvaiko P. Ontology Matching. Springer, 2007.

    Google Scholar 

  7. Gal A. Why is schema matching tough and what can we do about it? ACM SIGMOD Rec., 35(4):2–5, 2006.

    Google Scholar 

  8. Gal A., Anaby-Tavor A., Trombetta A., and Montesi D. A framework for modeling and evaluating automatic semantic reconciliation. VLDB J., 14(1):50–67, 2005.

    Google Scholar 

  9. Giunchiglia F., Marchese M., and Zaihrayeu I. Encoding classifications into lightweight ontologies. J. Data Semantics, 8:57–81, 2007.

    Google Scholar 

  10. Giunchiglia F. and Shvaiko P. Semantic Matching. Knowl. Eng. Rev., 18(3):265–280, 2003.

    Google Scholar 

  11. Giunchiglia F., Shvaiko P., and Yatskevich M. Discovering missing background knowledge in ontology matching. In Proc. 17th European Conf. on Artificial Intelligence, 2006, pp. 382–386.

    Google Scholar 

  12. Giunchiglia F., Yatskevich M., Avesani P., and Shvaiko P. A large scale dataset for the evaluation of ontology matching systems. Knowl. Eng. Rev., 23:1–22, 2008.

    Google Scholar 

  13. Giunchiglia F., Yatskevich M., and Shvaiko P. Semantic matching: algorithms and implementation. J. Data Semantics, 9:1–38, 2007.

    Google Scholar 

  14. Larson J., Navathe S., and Elmasri R. A theory of attributed equivalence in databases with application to schema integration. IEEE Trans. Software Eng., 15(4):449–463, 1989.

    MATH  Google Scholar 

  15. Madhavan J., Bernstein P., and Rahm E. Generic schema matching with Cupid. In Proc. 27th Int. Conf. on Very Large Data Bases, 2001, pp. 48–58.

    Google Scholar 

  16. Noy N. and Musen M. The PROMPT suite: interactive tools for ontology merging and mapping. Int. J. Hum. Comput. Stud., 59(6):983–1024, 2003.

    Google Scholar 

  17. Rahm E. and Bernstein P. A survey of approaches to automatic schema matching. VLDB J., 10(4):334–350, 2001.

    MATH  Google Scholar 

  18. Shvaiko P. and Euzenat J. A survey of schema-based matching approaches. J. Data Semantics, 4:146–171, 2005.

    Google Scholar 

  19. Spaccapietra S. and Parent C. Conflicts and correspondence assertions in interoperable databases. ACM SIGMOD Rec., 20(4):49–54, 1991.

    Google Scholar 

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Giunchiglia, F., Shvaiko, P., Yatskevich, M. (2009). Semantic Matching. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1044

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