(1999) Semantic heterogeneity resolution in federated databases by metadata implantation and stepwise evolution. In: Proceedings of SIGMOD, 2004Īslan G., McLeod D. In: VLDB, 2004Īndritsos, P., Miller, R.J., Tsaparas, P.: Information-theoretic tools for mining database structure from large data sets. 32(3): 138–140Īgrawal, S., Chaudhuri, S., Kollr, L., Marathe, A.P., Narasayya, V.R., Syamala, M.: Database tuning advisor for microsoft sql server 2005. (2003) Special issue on peer to peer data management. The results show that eTuner produced tuned matching systems that achieve higher accuracy than using the systems with currently possible tuning methods.Īberer K. We employed eTuner to tune four recently developed matching systems on several real-world domains. While the tuning process is completely automatic, eTuner can also exploit user assistance (whenever available) to further improve the tuning quality. To increase the applicability of eTuner, we develop methods to tune a broad range of matching components. To efficiently search the huge space of tuning configurations, eTuner works sequentially, starting with tuning the lowest level components.
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. We describe eTuner, an approach to automatically tune schema matching systems. Tuning is skill and time intensive, but (as we show) without it the matching accuracy is significantly inferior. 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). Most recent schema matching systems assemble multiple components, each employing a particular matching technique.
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