Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
920272 | Acta Psychologica | 2010 | 9 Pages |
Abstract
In this paper, we investigate the hypothesis that people use feature correlations to detect inter- and intra-categorical structure. More specifically, we study whether it is plausible that people strategically look for a particular type of feature co-occurrence that can be represented in terms of rectangular patterns of 1s and 0s in a binary feature by exemplar matrix. Analyzing data from the Animal and Artifact domains, we show that the HICLAS model, which looks for such rectangular structure and which therefore models a cognitive capacity of detecting feature co-occurence in large data bases of features characterizing exemplars, succeeds rather well in predicting inter- and intra-categorical structure.
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Authors
Eva Ceulemans, Gert Storms,