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Simulating Similarity-Based Retrieval: A Comparison of ARCS and MAC/FAC
Abstract
Current theories and supporting simulations of similaritybased retrieval disagree in their process model of semantic similarity decisions. We compare two current computational simulations of similarity-based retrieval, MAC/FA C and ARCS, with particular attention to the semantic similarity models used in each. Four experiments are presented comparing the performance of these simulations on a common set of representations. The results suggest that MAC/FAC, with its identicality-based ccmstraint on semantic similarity, provides a better account of retrieval than ARCS, with its similarity-table based model.
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