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论内隐分类的本质。

On the nature of implicit categorization.

作者信息

Ashby F G, Waldron E M

机构信息

Department of Psychology, University of California, Santa Barbara, CA 93106, USA.

出版信息

Psychon Bull Rev. 1999 Sep;6(3):363-78. doi: 10.3758/bf03210826.

Abstract

Current categorization models disagree about whether people make a priori assumptions about the structure of unfamiliar categories. Data from two experiments provided strong evidence that people do not make such assumptions. These results rule out prototype models and many decision bound models of categorization. We review previously published neuropsychological results that favor the assumption that category learning relies on a procedural-memory-based system, rather than on an instance-based system (as is assumed by exemplar models). On the basis of these results, a new category-learning model is proposed that makes no a priori assumptions about category structure and that relies on procedural learning and memory.

摘要

当前的分类模型对于人们是否会对不熟悉类别的结构做出先验假设存在分歧。来自两项实验的数据提供了有力证据,表明人们不会做出这样的假设。这些结果排除了分类的原型模型和许多决策边界模型。我们回顾了先前发表的神经心理学结果,这些结果支持这样一种假设,即类别学习依赖于基于程序记忆的系统,而不是基于实例的系统(如范例模型所假设的那样)。基于这些结果,我们提出了一种新的类别学习模型,该模型不对类别结构做先验假设,而是依赖于程序学习和记忆。

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