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Similarity as interactive activation and mapping (SIAM), a model of the dynamic course of similarity comparisons, is presented. According to SIAM, when structured scenes are compared, the parts of one scene must be aligned, or placed in correspondence, with the parts from the other scene. Emerging correspondences influence each other in a manner such that, with sufficient time, the strongest correspondences are those that are globally consistent with other correspondences. Relative to globally inconsistent feature matches, globally consistent feature matches influence similarity more when greater amounts of time are given for a comparison. A common underlying process model of scene alignment accounts for commonalities between different task conditions. Differences between task conditions are accounted for by principled parametric variation within the model.