A Model of Human Categorization and Similarity Based Upon Category Theory (original) (raw)

1994

Abstract The relation between similarity and categorization has recently come under scrutiny from several sectors. The issue provides an important inroad to questions about the contributions of high-level thought and lower-level perception in the development of people's concepts. Many psychological models base categorization on similarity, assuming that things belong in the same category because of their similarity.

Similarity and Categorization.'

1997

The intuitive idea that we classify together those things that we find similar has had a chequered history in psychology. While there was considerable theoretical and empirical development of similarity-based classification models in the 1970s (Medin & Schaffer, 1978; Rosch, 1975), subsequently there has been what might be termed a "rationalist backlash" against these models. In particular a number of researchers have questioned the degree to which the notion of similarity is sufficiently clearly defined and constrained to serve as an explanation of categorization.

Two mathematical models of human categorization

The goal of the paper is mathematical verification of various hypotheses concerning the cognitive efficiency of human categorization. To this aim two calculus-based mathematical models are constructed to account for the crucial features of human categorization: prototypicality and basic level primacy. The first model allows to calculate and compare the cognitive efficiency of the prototype and definition based categories, while the second one explicates the cognitive prominence of the basic level categories. Additionally, the models account for cultural and specialist knowledge variability of categorization as well as the link between the limited human brain capacity and categorization. Both models can be also be used to predict and extrapolate the results of psycho-linguistic experiments.

1998

Given the key importance of the concept of" similarity" for understanding analogy, the purpose of my paper will be to investigate a parallel issue-the role of similarity in understanding categorization. It may seem almost tautological to say that we categorize the world into categories of similar objects, persons or events. Similarity is after all merely an extension of the notion of" sameness". Similarity may just be sameness in respect of a particular set of features or dimensions.

Alternative strategies of categorization

Cognition, 1998

Psychological studies of categorization often assume that all concepts are of the same general kind, and are operated on by the same kind of categorization process. In this paper, we argue against this unitary view, and for the existence of qualitatively different categorization processes. In particular, we focus on the distinction between categorizing an item by: (a) applying a category-defining rule to the item vs. (b) determining the similarity of that item to remembered exemplars of a category. We begin by characterizing rule application and similarity computations as strategies of categorization. Next, we review experimental studies that have used artificial categories and shown that differences in instructions or time pressure can lead to either rule-based categorization or similarity-based categorization. Then we consider studies that have used natural concepts and again demonstrated that categorization can be done by either rule application or similarity calculations. Lastly, we take up evidence from cognitive neuroscience relevant to the rule vs. similarity issue. There is some indirect evidence from brain-damaged patients for neurological differences between categorization based on rules vs. that based on similarity (with the former involving frontal regions, and the latter relying more on posterior areas). For more direct evidence, we present the results of a recent neuroimaging experiment, which indicates that different neural circuits are involved when people categorize items on the basis of a rule as compared with when they categorize the same items on the basis of similarity.

1998

The adequacy of similarity to prototype as an account of categorization in natural concepts was assessed by analyzing the monotonicity of the relation between typicality of an item in a category and the probability of a positive categorization response using data from McCloskey and Glucksberg (1978). The analysis revealed a strong underlying similarity-based threshold curve, with systematic deviations.

Journal of Experimental Psychology: Learning, Memory, and Cognition, 1988

This article studies the joint roles of similarity and frequency in determining graded category structure. Perceptual classification learning experiments were conducted in which presentation frequencies of individual exemplars were manipulated. The exemplars had varying degrees of similarity to members of the target and contrast categories. Classification accuracy and typicality ratings increased for exemplars presented with high frequency and for members of the target category that were similar to the high-frequency exemplars. Typicality decreased for members of the contrast category that were similar to the high-frequency exemplars. A frequency-sensitive similarity-to-exemplars model provided a good quantitative account of the classification learning and typicality data. The interactive relations among similarity, frequency, and categorization are considered in the General Discussion.

The similarity choice model of identification (Lute, 1963; Shepard, 1957) and the context model of categorization (Medin & SchaNer, 1978; Nosofsky, 1986) are shown to be closely related to a variety of likelihood-based models. In particular, it is shown that: (1) for category distributions defined over independent dimensions, general versions of the context model and Estes' (1986) similarity-likelihood model are formally identical;

The development of feature spaces for similarity and categorization

1995

Similarity and categorization are usually formulated as operations over a set of available features at time t of conceptual development. In this paper, we discuss possible constraints on the development of the feature space such as the history of categorization, perceptual biases in the selection and the construction of features, and the role of higherlevel knowledge and beliefs. The history of categorization is defined as the feature vocabulary and the set of concepts people have acquired as a result of representing and categorizing objects. Perceptual and developmental biases refer to the salience of specific aspects of the stimuli which influence the selection and the construction of features at different stages of development. The constraining role of general knowledge on the selection and the creation of features is also discussed. It is argued that theories may need the constraints they are supposed to provide. We conclude by discussing issues related to the interactions of perceptions and conceptions in developing feature spaces for higher-level cognition.

A Model of Human Categorization and Similarity Based Upon Category Theory (original) (raw)

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