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Determining the correspondences among heterogeneous data sources, which is critical to integration of the data sources, is a complex and resource-consuming task that demands automated support. We propose an iterative procedure for detecting both schema-level and instance-level correspondences from heterogeneous data sources. Cluster analysis techniques are used first to identify similar schema elements (i.e., relations and attributes). Based on the identified schema-level correspondences,doi:10.1016/j.datak.2006.06.004 fatcat:l4yux53lfbh33nzomjosptjuya