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MedMatch – Towards Domain Specific Semantic Matching

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Conceptual Structures for Discovering Knowledge (ICCS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6828))

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Abstract

Ontologies are increasingly being used to address the problems of heterogeneous data sources. This has in turn often led to the challenge of heterogeneity between ontologies themselves. Semantic Matching has been seen as a potential solution to resolving ambiguities between ontologies . Whilst generic algorithms have proved successful in fields with little domain specific terminology, they have often struggled to be accurate in areas such as medicine which have their own highly specialised terminology. The MedMatch algorithm was initially created to apply semantic matching in the medical domain through the use of a domain specific background resource. This paper compares a domain specific algorithm (MedMatch) against a generic (S-Match) matching technique, before considering if MedMatch can be tailored to work with other background resources. It is concluded that this is possible, raising the prospect of domain specific semantic matching in the future.

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References

  1. Giunchiglia, F., Shvaiko, P.: Semantic Matching. The Knowledge Engineering Review 18(3), 265–280 (2003)

    Article  Google Scholar 

  2. Sartor, G., Casanovas, P., Casellas, N., Rubino, R.: Computable models of the law and ICT: State of the art and trends in european research. In: Casanovas, P., Sartor, G., Casellas, N., Rubino, R. (eds.) Computable Models of the Law. LNCS (LNAI), vol. 4884, pp. 1–20. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  3. Beisswanger, E., et al.: BioTop: An upper domain ontology for the life sciences: A description of its current structure, contents and interfaces to OBO ontologies. Appl. Ontol. 3, 205–212 (2008)

    Google Scholar 

  4. Euzenat, J., Shvaiko, P.: Ontology Matching. Springer, Heidelberg (2007)

    MATH  Google Scholar 

  5. Berners-Lee, T., et al.: The Semantic Web. Scientific American 284(5), 35–43 (2001)

    Article  Google Scholar 

  6. Stoilos, G., Stamou, G., Kollias, S.D.: A String Metric for Ontology Alignment. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 624–637. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  7. Doan, A., et al.: Ontology Matching: A Machine Learning Approach. In: Handbook on Ontologies in Information Systems, pp. 385–403 (2004)

    Google Scholar 

  8. Madhavan, J., et al.: Generic schema matching using cupid. In: 27th International Conference on VLDB, pp. 49–58 (2001)

    Google Scholar 

  9. Tan, H., Jakonienė, V., Lambrix, P., Aberg, J., Shahmehri, N.: Alignment of Biomedical Ontologies Using Life Science Literature. In: Bremer, E.G., Hakenberg, J., Han, E.-H(S.), Berrar, D., Dubitzky, W. (eds.) KDLL 2006. LNCS (LNBI), vol. 3886, pp. 1–17. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  10. Risto, G., et al.: Using Google Distance to Weight Approximate Ontology Matches. In: BNACI 2007 (2007)

    Google Scholar 

  11. Giunchiglia, F., et al.: Semantic Matching: Algorithms and Implementation. Journal on Data Semantics 9, 1–38 (2007)

    MATH  Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Shamdasani, J., Bloodsworth, P., Munir, K., Rahmouni, H.B., McClatchey, R. (2011). MedMatch – Towards Domain Specific Semantic Matching. In: Andrews, S., Polovina, S., Hill, R., Akhgar, B. (eds) Conceptual Structures for Discovering Knowledge. ICCS 2011. Lecture Notes in Computer Science(), vol 6828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22688-5_33

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  • DOI: https://doi.org/10.1007/978-3-642-22688-5_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22687-8

  • Online ISBN: 978-3-642-22688-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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