The VLDB Journal

, Volume 16, Issue 1, pp 97–122

eTuner: tuning schema matching software using synthetic scenarios

  • Yoonkyong Lee
  • Mayssam Sayyadian
  • AnHai Doan
  • Arnon S. Rosenthal
Special Issue Paper

DOI: 10.1007/s00778-006-0024-z

Cite this article as:
Lee, Y., Sayyadian, M., Doan, A. et al. The VLDB Journal (2007) 16: 97. doi:10.1007/s00778-006-0024-z

Abstract

Most recent schema matching systems assemble multiple components, each employing a particular matching technique. The domain user mustthen tune the system: select the right component to be executed and correctly adjust their numerous “knobs” (e.g., thresholds, formula coefficients). Tuning is skill and time intensive, but (as we show) without it the matching accuracy is significantly inferior. We describe eTuner, an approach to automatically tune schema matching systems. Given a schema S, we match S against synthetic schemas, for which the ground truth mapping is known, and find a tuning that demonstrably improves the performance of matching S against real schemas. To efficiently search the huge space of tuning configurations, eTuner works sequentially, starting with tuning the lowest level components. To increase the applicability of eTuner, we develop methods to tune a broad range of matching components. While the tuning process is completely automatic, eTuner can also exploit user assistance (whenever available) to further improve the tuning quality. We employed eTuner to tune four recently developed matching systems on several real-world domains. The results show that eTuner produced tuned matching systems that achieve higher accuracy than using the systems with currently possible tuning methods.

Keywords

Schema matchingTuningSynthetic schemasMachine learningCompositional approach

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Yoonkyong Lee
    • 1
  • Mayssam Sayyadian
    • 1
  • AnHai Doan
    • 1
  • Arnon S. Rosenthal
    • 2
  1. 1.University of IllinoisUrbanaUSA
  2. 2.The MITRE CorporationBedfordUSA