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In this paper, we present a "value mapping" algorithm that does not rely on syntactic similarity or semantic interpretation of the values. The algorithm first constructs a statistical model (e.g., co-occurrence frequency or entropy vector) that captures the unique characteristics of values and their co-occurrence. It then finds the matching values by computing the distances between the models while refining the models using user feedback through iterations. Our experimental results suggest thatdoi:10.1145/1099554.1099569 dblp:conf/cikm/KangHLM05 fatcat:vlfao5n3n5e6hgak532idtuk4e