Proceedings 18th International Conference on Data Engineering (2002)
San Jose, California
Feb. 26, 2002 to Mar. 1, 2002
Sergey Melnik , Stanford University
Hector Garcia-Molina , Stanford University
Erhard Rahm , University of Leipzig, Germany
Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs (schemas, catalogs, or other data structures) as input, and produces as output a mapping between corresponding nodes of the graphs. Depending on the matching goal, a subset of the mapping is chosen using filters. After our algorithm runs, we expect a human to check and if necessary adjust the results. As a matter of fact, we evaluate the `accuracy' of the algorithm by counting the number of needed adjustments. We conducted a user study, in which our accuracy metric was used to estimate the labor savings that the users could obtain by utilizing our algorithm to obtain an initial matching. Finally, we illustrate how our matching algorithm is deployed as one of several high-level operators in an implemented testbed for managing information models and mappings.
Matching, Model Management, Heterogeneous Databases, Semistructured Data
H. Garcia-Molina, S. Melnik and E. Rahm, "Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching," Proceedings 18th International Conference on Data Engineering(ICDE), San Jose, California, 2002, pp. 0117.