Similarity and Categorization

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ISBN: 9780198506287 | 0198506287
Cover: Hardcover
Copyright: 6/7/2001

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Understanding how objects are partitioned into useful groups to form concepts is important to most disciplines. Concepts allow us to treat different objects equivalently according to shared attributes, and hence to communicate about, draw inferences from, reason with, and explain theseobjects. Understanding how concepts are formed and used is thus essential to understanding and applying these basic processes, and the topic of similarity-based classification is central to psychology, artificial intelligence, statistics, and philosophy. Similarity and Categorisation provides auniquely interdisciplinary overview of this area. The book brings together leading researchers, reflecting the key topics and important developments in the field. It will be of interest to researchers and graduate students within the areas of cognitive psychology, artificial intelligence, andphilosophy.

Contributors

Introduction: similarity and categorization

(12)

Ulrike Hahn

Michael Ramscar

Similarity and categorization

(1)

Categorization and similarity

(2)

The `what' of similarity and categorization: concepts and categories

(1)

The `why' of similarity and categorization

(1)

The role of similarity in categorization: the structre of this book

(3)

Other ways to read this book

(1)

References

(3)

The role of similarity in natural categorization

(16)

James A. Hampton

Similarity-based categorization

(7)

Evidence for similarity in categorization

(1)

Does categorization depend only on typicality?

(3)

What role does similarity play?

(2)

Acknowledgements

(1)

References

(3)

Induction and inherent similarity

(22)

T. Mark Ellison

Introduction

(1)

Attributes, predicates, and categories

(1)

Dark matter

(2)

Stabs into the dark

(1)

A new approach

(2)

Topographic mappings

(3)

Untopographic grue

(3)

Extrapolation, category transfer, and prototypes

(3)

Discussion

(3)

Acknowledgements

(1)

References

(3)

Categorization by simplicity: a minimum description length approach to unsupervised clustering

(22)

Emmanuel M. Pothos

Nick Chater

Introduction

(2)

Categorization and induction

(2)

Overview of clustering

(3)

Clustering by simplicity

(3)

Artificial data sets

(5)

Psychological data sets

(2)

Conclusions and future directions

(1)

Acknowledgements

(1)

References

(4)

Categorization versus similarity: the case of container names

(14)

Steven A. Sloman

Barbara C. Malt

Arthur Fridman

Introduction

(1)

The studies

(8)

Conclusions

(3)

Acknowledgements

(1)

References

(2)

Dissociation between categorization and similarity judgement: differential effect of causal status on feature weights

(22)

Woo-kyoung Ahn

Martin J. Dennis

Introduction

(2)

Previous demonstrations of dissociations between similarity and categorization

(1)

The causal status hypothesis

(2)

Study 1: does the causal status effect occur in similarity judgements?

(2)

Causal status effect in similarity and categorization judgements

(1)

Methodological accounts of dissociations between categorization and similarity judgements

(2)

Study 2: dissociations between similarity and categorization (1)

(2)

Study 3: dissociations between similarity and categorization (2)

(1)

Methodological accounts reconsidered

100

(1)

Study 4: similarity can correlate with categorization

101

(3)

Summary of experiments

104

(1)

Similarity and categorization

105

(1)

Acknowledgements

106

(1)

References

106

(3)

Structural alignment, similarity, and the internal structure of category representations

109

(22)

Arthur B. Markman

Introduction

109

(1)

Structural alignment in similarity

109

(8)

Studying categorization in the laboratory

117

(8)

Conclusions

125

(1)

Acknowledgements

125

(1)

References

126

(5)

Issues in case-based reasoning

131

(24)

Abraham Rodriguez Rodriguez

Introduction

131

(2)

What is a case?

133

(1)

How CBR systems work

134

(2)

Similarity

136

(6)

Hybrid systems

142

(5)

Generic tasks

147

(2)

Summary

149

(1)

Acknowledgements

150

(1)

References

150

(5)

Background knowledge and models of categorization

155

(24)

Evan Heit

Introduction

155

(1)

The integration model

156

(1)

Overview of experiments to be analysed

157

(1)

Wattenmaker et al. (1986), Experiment 3

158

(2)

Pazzani (1991), Experiment 1

160

(2)

Barrett et al. (1993)

162

(3)

Murphy and Allopenna (1994)

165

(4)

General discussion

169

(5)

Acknowledgements

174

(1)

References

174

(2)

Appendix

176

(3)

Dynamic similarity: a processing perspective on similarity

179

(14)

Mark T. Keane

Barry Smyth

Joseph O'Sullivan

Introduction

179

(1)

Static similarity theories

180

(1)

Manifestations of dynamic similarity

181

(1)

Dynamic similarity I: comparing event descriptions

182

(3)

Dynamic similarity II: swapping history in perceptual patterns

185

(4)

Dynamic similarity III: similarity in the future

189

(1)

Conclusion

190

(1)

References

190

(3)

The time course of perceptual categorization

193

(32)

Thomas J. Palmeri

Introduction

193

(1)

Reasons to investigate the time course of categorization

194

(1)

A formal model of categorization: the generalized context model

195

(4)

The extended generalized context model

199

(5)

The exemplar-based random walk model

204

(15)

Summary

219

(1)

Acknowledgements

219

(1)

References

219

(6)

Interactions between taxonomic knowledge, categorization, and perception

225

(32)

Frederic Gosselin

Annie Archambault

Philippe G. Schyns

Introduction

225

(2)

Diagnostic recognition: an overview

227

(3)

Slip: a formal model of task constraints

230

(3)

Effects of taxonomy on categorization: basic-level performance

233

(10)

Effects of taxonomies on perception

243

(4)

General discussion

247

(3)

Concluding remarks

250

(1)

Acknowledgements

250

(1)

References

250

(4)

Appendix: a formal implementation of SLIP

254

(3)

Conclusion: mere similarity?

257

(16)

Ulrike Hahn

Michael Ramscar

Introduction

257

(3)

Is similarity too vague to be useful?

260

(1)

Is similarity too limited to be useful?

261

(1)

Similarity, coherence, and induction

262

(1)

Do theories fit the bill?

263

(3)

Can similarity serve as an adequate basis for induction?

266

(2)

The relationship between theories and similarity

268

(1)

Conclusion

269

(1)

Acknowledgements

270

(1)

References

270

(3)

Index

273

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Similarity and Categorization

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Table of Contents

Supplemental Materials