Categorization in well-known natural concepts is studied using a special version of the Varying Abstraction Frame-work (Vanpaemel, W., & Storms, G. (2006). A varying abstraction framework for categorization. Manuscript submit-ted for publication; Vanpaemel, W., Storms, G., & Ons, B. (2005). A varying abstraction model for categorization. In B. Bara, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the 27th annual conference of the Cognitive Science Soci-memory representations (prototypes) and highly detailed representations of concept members (exemplars). Comparison stimuli for categorization are obtained by taking for each category the centroids of a set of clusters, produced by K-means clustering, effectively producing ...
Do humans and animals learn exemplars or prototypes when they categorize objects and events in the w...
Early theories of categorization assumed that either rules, or prototypes, or exemplars were exclusi...
We present a connectionist model of concept learning that integrates prototype and exemplar effects ...
Categorization in well-known natural concepts is studied using a special version of the Varying Abst...
In this paper we propose, instead of the traditional distinction between prototype and exemplar mode...
The ability to learn categories and classify new items or experiences is an essential function for e...
We re-analyzed thirty data sets reported in the literature and summarized by Smith and Minda (2000),...
Cognition and categorization /edited by Rosch, E. and Lloyd, B., 1978 The papers in this book derive...
In this paper we introduce a new machine learning system developed to investigate the phenomenon of ...
Over the past four decades, two distinct alternatives have emerged to rule-based models of how lingu...
Concept learning and organization are much studied in artificial intelligence and cognitive psycholo...
Artificial Intelligence (AI) methods for machine learning can be viewed as forms of exploratory data...
This thesis describes a research programme on machine learning, based on the fundamental process of ...
The multivariate theory of similarity discussed by Ennis (1988) entails the assumption that individu...
Previously published sets of classification and old-new recognition memory data are reanalyzed withi...
Do humans and animals learn exemplars or prototypes when they categorize objects and events in the w...
Early theories of categorization assumed that either rules, or prototypes, or exemplars were exclusi...
We present a connectionist model of concept learning that integrates prototype and exemplar effects ...
Categorization in well-known natural concepts is studied using a special version of the Varying Abst...
In this paper we propose, instead of the traditional distinction between prototype and exemplar mode...
The ability to learn categories and classify new items or experiences is an essential function for e...
We re-analyzed thirty data sets reported in the literature and summarized by Smith and Minda (2000),...
Cognition and categorization /edited by Rosch, E. and Lloyd, B., 1978 The papers in this book derive...
In this paper we introduce a new machine learning system developed to investigate the phenomenon of ...
Over the past four decades, two distinct alternatives have emerged to rule-based models of how lingu...
Concept learning and organization are much studied in artificial intelligence and cognitive psycholo...
Artificial Intelligence (AI) methods for machine learning can be viewed as forms of exploratory data...
This thesis describes a research programme on machine learning, based on the fundamental process of ...
The multivariate theory of similarity discussed by Ennis (1988) entails the assumption that individu...
Previously published sets of classification and old-new recognition memory data are reanalyzed withi...
Do humans and animals learn exemplars or prototypes when they categorize objects and events in the w...
Early theories of categorization assumed that either rules, or prototypes, or exemplars were exclusi...
We present a connectionist model of concept learning that integrates prototype and exemplar effects ...