Relcon: A Tensor Model of Relational Categorization
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The Relcon algorithm models category formation using relational storage and retrieval mechanisms with a Tensor memory. Relcon settles on a category structure that matches prototypicality characteristics of human categories. A tensor intersection operation simulates the influence of context on category structure and on similarity. The results have implications for models of binding and representation, and provide a framework for answering the current call for relationbased representations for categories.
Proceedings of the 28th Annual Conference of the Cognitive Science Society in cooperation with the 5th International Conference of Cognitive Science
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