Relcon: A Tensor Model of Relational Categorization

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Author(s)
Gray, Brett
H. Wilson, William
Halford, Graeme
McCredden, J.
Griffith University Author(s)
Year published
2006
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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.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.
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Conference Title
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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Copyright Statement
© The Author(s) 2006. The attached file is posted here with permission of the copyright owners for your personal use only. No further distribution permitted. For information about this conference please refer to the publisher's website or contact the authors.