Abstract

Previously published sets of classification and old-new recognition memory data are reanalyzed within the framework of an exemplar-based generalization model. The key assumption in the model is that, whereas classification decisions are based on the similarity of a probe to exemplars of a target category relative to exemplars of contrast categories, recognition decisions are based on overall summed similarity of a probe to all exemplars. The summed-similarity decision rule is shown to be consistent with a wide variety of recognition memory data obtained in classification learning situations and may provide a unified approach to understanding relations between categorization and recognition. Recently, there has been an upsurge of interest among categorization researchers in exploring relations between classification learning and old-new recognition memory. This interest has been fueled by the exemplar view of category representation, which holds that people base classification decisions on similarity comparisons with stored exemplars (Hintzman, 1986b; Medin & Schaffer, 1978; Nosofsky, 1986).

Citations

312	M.M.: Context theory of classification learning - Medin, Schaffer - 1978
299	Attention, similarity, and the identificationcategorization relationship - Nosofsky - 1986
232	Toward a universal law of generalization for psychological science - Shepard - 1987
170	The processing of information and structure - Garner - 1974
116	Scheme abstraction in a multiple-trace memory model - Hintzman - 1986
115	Pattern recognition and categorization - Reed - 1972
109	Decision rules in perception and categorization of multidimensional stimuli - Ashby, Gott - 1988
96	Choice, similarity, and the context theory of classification - Nosofsky - 1984
88	Judgments of frequency and recognition memory in a multiple-trace memory model - Hintzman - 1988
75	A retrieval model for both recognition and recall - Gillund, Schiffrin - 1984
65	Recognizing: The judgment of previous occurrence - Mandler - 1980
64	Attention and learning processes in the identification and categorization of integral stimuli - Nosofsky - 1987
50	Attention and the metric structure of the stimulus space - Shepard - 1964
47	Similarity, frequency, and category representations - Nosofsky - 1988
41	Array models for category learning - Estes - 1986
32	Problem structure and the use of base-rate information from experience - Medin, Edelson - 1988
24	Search and decision processes in recognition memory - Atkinson, Juola - 1974
22	Stimulus and response generalization: Deduction of the generalization gradient from a trace model - Shepard - 1958
21	Memory storage and retrieval processes in category learning - EsTes - 1986
20	Concept learning and the recognition and classification of exemplars - HAYES-ROTH, HAYES-ROTH - 1977
19	Limitations of exemplar-based generalization and the abstraction of categorical information - Homa, Sterling, et al. - 1981
17	Evaluation of exemplar-based generalization and the abstraction of categorical information - Busemeyer, Dewey, et al. - 1984
15	Discrimination and generalization in identification and classification: Comment on Nosofsky - Shepard - 1986
13	A general learning theory and its application to schema abstraction - Anderson, Kline, et al. - 1979
7	Typicality effect in logically defined categories - Bourne - 1982
4	Commentary on "Memory storage and retrieval processes in category learning - Medin - 1986
4	Recognition vs. classification of ill-defined category exemplars - Omohundro - 1981
3	Cue-context interactions in discrimination, categorization and memory - Medin, Reynolds - 1985
2	Retrieval processes in recognition memory - Tulving, Thomson - 1971