Automatch Revisited

  • Amihai MotroEmail author


We revisit the Autoplex and Automatch projects from 2001–2005, and in particular the results reported in the paper Database Schema Matching Using Machine Learning with Feature Selection, presented in the 14th International Conference on Advanced Information Systems Engineering (2002). We provide the motivation and background for these projects, examine their impact a decade later, and sketch possible research directions.


Global Schema Information Item Database Schema Query Answering Query Translation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The original paper was co-authored by Jacob Berlin, who was my doctoral student at that time. Jake deserves an equal share of the credit for the work that we have accomplished. Unfortunately, I was unable to contact Jake for the purpose of this article.


  1. 1.
    Andreasen, T., Christiansen, H., Larsen, H.L. (Editors). Flexible Query Answering Systems. Kluwer Academic Publishers, 1997.Google Scholar
  2. 2.
    Batini, C., Lenzerini, M., Navathe, S.B. A comparative analysis of methodologies for database schema integration. Computing Surveys, 18(4):323–364, 1989.CrossRefGoogle Scholar
  3. 3.
    Berlin, J., Motro, A. Autoplex: Automated discovery of contents for virtual databases. In Proceedings of COOPIS 01, Sixth IFCIS International Conference on Cooperative Information Systems, Trento, Italy. Lecture Notes in Computer Science No. 2172, pp. 108–122, 1999.Google Scholar
  4. 4.
    Church, J., Motro, A. Learning service behavior with progressive testing. In Proceedings of SOCA 11, IEEE International Conference on Service-Oriented Computing and Applications, Irvine, CA, USA. pp. 1–8, 2011.Google Scholar
  5. 5.
    Etzioni, O., Halevy, A., Doan, A., Ives, Z.G, Madhaven, J., McDowell, L., Tatarinov, I. Crossing the structure chasm. In Proceedings of CIDR-03, First Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA., 2003. Available online at
  6. 6.
    Garcia-Molina, H., Papakonstantinou, Y., Rajaraman, A., Sagiv, Y., Ullman, J., Vassalos, V., Widom, J. The TSIMMIS approach to mediation: data models and languages. Journal of Intelligent Information Systems, 8(2):117–132, 1997.CrossRefGoogle Scholar
  7. 7.
    Miller, R.J., Hernandez, M.A., Haas, L.M., Yan, L., Ho, C.T.H., Fagin, R., Popa, L. The Clio project: managing heterogeneity. SIGMOD Record 30(1):78–83, 2001.CrossRefGoogle Scholar
  8. 8.
    Motro, A. Interrogating superviews. In Proceedings of ICOD-2, Second International Conference on Databases, Cambridge, England, pp. 107–126, 1981.Google Scholar
  9. 9.
    Motro, A., Smets, P. Uncertainty Management in Information Systems: from Needs to Solutions. Kluwer Academic Publishing, 1996.Google Scholar
  10. 10.
    Motro, A. Multiplex: a formal model for multidatabases and its implementation. In Proceedings of NGITS 96, Fourth International Workshop on Next Generation Information Tecnologies and Systems, Zichron Yaacov, Israel. Lecture Notes in Computer Science No. 1649, pp. 138–158, 1999.Google Scholar
  11. 11.
    Rahm, E., Bernstein, P.A. A survey of approaches to automatic schema matching. The VLDB Journal, 10(4), pp. 334–350, 2001.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Computer Science DepartmentGeorge Mason UniversityFairfaxUSA

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