Unifying rational models of categorization via the hierarchical Dirichlet process
Griffiths, Thomas L., Canini, Kevin R., Sanborn, Adam N. and Navarro, Daniel J. (2009) Unifying rational models of categorization via the hierarchical Dirichlet process. In: Proceedings of the 29th Annual Conference of the Cognitive Science Society. Lawrence Erlbaum, Mahwah, N.J., p. 323. ISBN 9781605605074Full text not available from this repository.
Models of categorization make different representational assumptions, with categories being represented by prototypes, sets of exemplars, and everything in between. Rational models of categorization justify these representational assumptions in terms of different schemes for estimating probability distributions. However, they do not answer the question of which scheme should be used in representing a given category. We show that existing rational models of categorization are special cases of a statistical model called the hierarchical Dirichlet process, which can be used to automatically infer a representation of the appropriate complexity for a given category.
|Item Type:||Book Item|
|Subjects:||B Philosophy. Psychology. Religion > BF Psychology|
|Divisions:||Faculty of Science > Psychology|
|Place of Publication:||Mahwah, N.J.|
|Book Title:||Proceedings of the 29th Annual Conference of the Cognitive Science Society|
|Page Range:||p. 323|
|Conference Paper Type:||Paper|
|Title of Event:||CogSci 2007: The 29th Annual Conference of the Cognitive Science Society|
|Type of Event:||Conference|
|Location of Event:||Nashville, USA|
|Date(s) of Event:||1-4 Aug 2007|
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