Handbook of categorization in cognitive science:
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| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Amsterdam u.a.
Elsevier
2005
|
| Edition: | 1. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXXV, 1087, 11 ungez S. Ill., graph. Darst. |
| ISBN: | 0080446124 |
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| 650 | 4 | |a Sciences cognitives | |
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| adam_text | TABLE OF CONTENTS
See Color Plate Section at the back of this book
Preface v
Bridging the Category Divide
HENRI COHEN and CLAIRE LEFEBVRE
1. Introduction 2
2. Organization of the book 2
3. Major common themes 7
3.1. The notions of category and eategorization 7
3.2. The nuturc of catcgorics: Diserete, vague, or other 9
3.3. Are there modality ei feets on eategories? 10
3.4. Are there universal eategories? Are there innate eategories? 11
4. Bridging the category divide 13
References 15
PART 1 CATEGORIZATION IN COGNITIVE SCIENCE
Chapter 1
To Cognize is to Categorize: Cognition is Categorization
STEVAN HARNAD
Abstract 20
1. Sensorimotor Systems 21
2. Invariant sensorimotor features ( affordances ) 21
3. Categorization 21
4. Learning 22
5. Innate eategories 23
6. Learned eategories 23
7. Supervised learning 24
8. Instrumental (operant) learning 24
9. Color eategories 25
10. Categorical pereeption 25
11. Learning algorithms 26
12. Unsupervised learning 27
13. Supervised learning 27
14. Vanishing intersections? 28
15. Direct sensorimotor invariants 29
vii
16. Abstraction and hearsay 30
17. Abstraction and amnesia 30
18. Invariance and recurrence 31
19. Feature selection and weighting 32
20. Discrimination versus categorization 32
21. Recoding and feature selection 33
22. Learned categorical perception and the Whorf hypothesis 34
23. Uncertainty reduction 35
24. Explicit learning 36
25. Categorization is abstraction 36
26. Sensorimotor grounding: direct and derivative 36
27. The adaptive advantage of language: hearsay 37
28. Absolute discriminables and affordances 39
29. Cognitive science is not ontology 39
30. Cognition is categorization 40
Appendix A. There is nothing wrong with the classical theory of categorization 40
Appendix B. Associationism begs the question of categorization 41
References 42
Chapter 2
A Modular Approach to Grammatical Categories Evidence from
Language Diversity and Contact
PIETER MUYSKEN
Abstract 46
1. Introduction 47
2. Modularity and mismatch 48
3. Grammaticalization: The case of pe in Sranan (Suriname) 52
4. Mismatches in complexity of representations:
The case of ku in Cuzco Quechua (Peru) 54
5. Lexical nondistinctness 55
5.1. The case of timap in Palikur 55
5.2. For prepositions to become complementizers 56
5.3. Adjectives versus adverbs 57
6. Lexical overspecification: Dutch gender and definiteness 57
7. The Status of null elements: Subjects in Sranan and Papiamentu 58
8. Partially overlapping categories: predicate adjectives in Creoles 59
9. Differences in lexical richness 60
10. Evidence from language contact 61
10.1. Otomanguean Spanish language contact 62
10.2. Borrowing of Content words in Salishan languages 65
11. Concluding remarks 67
Appendix 67
References 68
Chapter 3
Philosophical Analysis as Cognitive Psychology: The Case of Empty Concepts
GEORGES REY
Abstract 72
1. Introduction 73
2. Misadventures of the Classical View 73
3. Terminological issues 75
3.1. Existential vs. (purely) intentional usage 75
3.2. Concepts as between representations and referents 77
4. The inadequacies of Extemalism 77
5. The need for internal roles 82
5.1. The Quinean challenge 82
5.2. The analytic data 83
5.3. Rivals to the Analytic Explanation 85
6. Conclusion 87
References 88
Chapter 4
Categories and Cognitive Anthropology
JAMES S. BOSTER
Abstract 92
1. Introduction 93
2. Cognition and culture, universalism and relativism 93
3. Paradigms and taxonomies 94
4. Kinship terminologies 101
5. Color classification 105
6. Ethnobiology 109
7. Towards a science of the Stimulus 114
References 116
Chapter 5
Categorization in Neuroscience: Brain Response to Objects and Events
CATHERINE HANSON and STEPHEN JOSE HANSON
Abstract 119
1. Introduction 120
2. Representing object categories in the brain 121
2.1. Category specific representation 122
2.2. Feature specific representation 123
2.3. Process specific representation 125
2.4. Summary 125
3. Acquiring category knowledge 126
3.1. Summary 130
4. Categorizing actions and events 130
4.1. The nature of event knowledge 130
4.2. When categorization of action fails 132
4.3. The perception of events 133
4.4. Summary 136
5. Conclusion 136
References 137
Chapter 6
Categorization in Cognitive Computer Science
JOHN F. SOWA
Abstract 141
1. Computation in cognitive science 142
2. The great categorization debates 144
3. From local features to global structures 148
4. Categorization and reasoning 153
5. Levels of cognition 158
References 161
PART 2 SEMANTIC CATEGORIES
Chapter 7
Semantic Categorization
BRENDAN S. GILLON
Abstract 167
1. Introduction 168
2. The notional approach to lexical categories 169
3. The notional approach to lexical subcategories 170
4. Structural approach to semantic categories 172
5. Coordinators and subordinators 175
6. Englishnouns 181
7. Conclusion 184
Acknowledgments 184
References 184
Chapter 8
Emotion Categories across Languages
JAMES S. BOSTER
Abstract 188
1. Introduction 189
2. Methods of assessing cultural emotion Systems 191
2.1. The Methodof Translation 191
2.2. TheMethodofMapping 198
3. Theories of emotion 210
4. Cross cultural scenarios as a tool to compare emotion categories 213
5. Conclusion 218
References 220
Chapter 9
The World Color Survey Database
RICHARD S. COOK, PAUL KAY and TERRY REGIER
Abstract 224
1. Introduction 225
2. The WCS: History and methodology 225
3. Data processing and analysis 228
4. Cleaning the data 232
5. Original format of the data and creation of the WCS Online Data Archive 232
6. Uses of the WCS archive 234
6.1. Universals of color naming 234
6.2. Variation in color naming 237
7. Conclusion 240
References 240
Chapter 10
Atoms, Categorization and Conceptual Change
PAUL THAGARD and ETHAN TOOMBS
Abstract 243
1. Introduction 244
2. Theories of concepts 245
3. The ancient concept of an atom 246
4. Revival of the concept of the atom 248
5. Modern development of the concept of an atom 249
6. Theories and meaning 252
7. Conclusion 253
References 253
Chapter 11
Relations between Language and Thought: Individuation and the Count/Mass
Distinction
ANNA PAPAFRAGOU
Abstract 256
1. Introduction 257
2. Strong discontinuity proposals 260
2.1. Quine 260
2.2. Abstract individuation in language and thought 262
3. Weak discontinuity proposals 263
3.1. Crosslinguistic studies ¦iOJ
3.2. Language on language efifects 266
4. Material and shape cues in labeling and categorization 268
5. Conclusion 271
References 271
Chapter 12
Definitions in Categorization and Similarity Judgments
SERGE LAROCHELLE, DENIS COUSINEAU and ANNE
ARCHAMBAULT
Abstract 278
1. Introduction 279
2. Importance rating and property selection 284
2.1. Method 284
2.2. Results 286
3. Categorization judgments 288
3.1. Method 288
3.2. Results 290
3.3. Discussion 296
4. Similarity judgments 297
4.1. Method 297
4.2. Results 298
5. General discussion 300
References 302
Chapter 13
Why (Most) Concepts aren t Categories
RUTH GARRETT MDLLIKAN
Abstract 305
1. Introduction 306
2. Species are not categories 306
3. Three kinds of (Aristotelian) substances 307
3.1. Historical kinds 307
3.2. Eternal kinds 308
3.3. Individuais 309
4. Concepts of individuals 310
5. Concepts of substances more generally 311
6. Substances encountered through language 312
References 315
PART 3 SYNTACTIC CATEGORIES
Chapter 14
Lexical, Functional, Crossover, and Multifunctional Categories
LISA DEMENA TRAVIS
Abstract 320
1. Introduction 321
2. Categories as feature bundles 321
2.1. The System 321
2.2. Natural classes 322
2.3. Unnatural classes 324
3. Categories and phrase structure 325
3.1. Lexical and functional categories 326
3.2. Articulation of functional categories 327
3.3. Articulation below N and V 329
3.4. Crossover and multifunctionality 330
4. Where do categorial distinctions reside? 336
5. Conclusions 344
References 345
Chapter 15
Isolating Monocategorial AssociationalLanguage
DAVID GIL
Abstract 348
1. Introduction 349
2. What IMA Language is Like 349
2.1. Isolating 350
2.2. Monocategorial 350
2.3. Associational 351
3. Where IMA Language Is Found 354
3.1. Semiotics 354
3.2. Phylogeny 356
3.3. Ontogeny 358
4. Typology 359
4.1. Riau Indonesian: overview 360
4.2. Riau Indonesian: analysis 364
4.3. Riau Indonesian: A Relative IMA Language 374
5. Cognition 375
Acknowledgments 377
References 377
Chapter 16
Categories in Quebec Sign Language: Reflections on Categorization
across Modalities
DENIS BOUCHARD, COLETTE DUBUISSON
and ANNE MARIE PARISOT
Abstract 381
1. The categories of lexical items 382
2. Traditional categorization applied to LSQ 384
2.1. Nouns and verbs 387
2.2. Pronouns and defmite determiners 387
3. Pronouns in oral languages and in sign languages 388
3.1. The effects of perceptual substances on linguistic forms 389
3.2. Explaining the different properties 390
4. Consequences for linguistic categorization and universals 396
References 398
Chapter 17
Syntactic Categories in Signed versus Spoken Languages
DIANE LILLO MARTIN
Abstract 402
1. Introduction 403
2. Lexical categories 403
3. Grammatical structures 405
3.1. Subordination 405
3.2. Spatial syntax 406
3.3. Word order 413
4. Conclusion 417
Acknowledgments 418
Appendix. Notational Conventions 418
References 419
Chapter 18
On Syntactic Categories
MARK C. BAKER 423
PART 4 ACQUISITION OF CATEGORIES
Chapter 19
The Acquisition of Grammatical Categories: the State of the Art
MARIE LABELLE
Abstract 433
1. Grammatical categories 434
2. Two word utterances and their analysis 435
3. A semantic approach to grammatical categorization:
Semantic bootstrapping 436
4. Distributional learning 439
4.1. Word order 439
4.2. Inflection and inflectional class 441
4.3. Function words 445
4.4. Word classes 447
4.5. Other cues to grammatical category learning 449
5. Models of distributional learning 449
6. Constraining the search space 450
7. Conclusion 451
References 452
Chapter 20
Semantic Categories in Acquisition
EVE VIVIENNE CLARK
Abstract 459
1. Introduction 460
2. Space 461
3. Shape 465
4. Adding common ground 466
5. Conceptual domains and lexical options 467
6. Adding meaning in the course of
conversation 472
7. Universals in mapping? 473
8. Conclusion 476
References 477
Chapter 21
Early Syntactic Categories in Infants Language
RUSHEN SHI
Abstract 481
1. Introduction 482
2. The acquisition of grammatical categories and the earliest binary
distinction of function words and content words 482
3. Input Speech and the categorization of function words
and content words 486
4. Function words and language acquisition 488
5. Conclusions 492
Acknowledgment 492
References 493
Chapter 22
Acquiring Auditory and Phonetic Categories
MARTDN GOUDBEEK, ROEL SMTTS, ANNE CUTLER
and DANIEL SWINGLEY
Abstract 497
1. Introduction 498
2. Testing category learning 500
3. Learning ofnonspeech categories 502
4. Learning of Speech categories 506
5. Conclusion 510
References 511
Chapter 23
Syntactic Categories in Second Language Acquisition
LYDIA WHITE
Abstract 515
1. Introduction 516
2. Lexical and functional categories 516
3. Lexical categories in L2 acquisition 517
4. Functional categories in acquisition: Issues of evidence 519
5. Functional categories in the L2 initial State and in L2 development 522
5.1. Morphology before syntax 522
5.2. Syntax before morphology 523
6. Acquiring versus losing categories and features 524
7. Discussion 529
References 530
Chapter 24
The Development of Categories in the Linguistic and
Nonlinguistic Domains: the Same or Different?
DIANE POULIN DUBOIS 535
PART 5 NEUROSCD3NCE OF CATEGORIZATION AND CATEGORY LEARNING
Chapter 25
Multiple Systems of Perceptual Category Learning: Theory and Cognitive Tests
F. GREGORY ASHBY and VIVIAN V. VALENTIN
Abstract 548
1. Introduction 549
2. Two Category Learning Tasks 550
3. COVIS 550
4. The COVIS explicit System 552
4.1. Switching attention in the explicit System 554
4.2. Long term storage of explicit category knowledge 556
iwi/ic yj i^wttcfuj XV11
5. The COVIS procedural learning system 557
6. Competition between the COVIS explicit and implicit Systems 560
7. Dissociations between rule based and inforaiation integration
category learning 561
8. Conclusions 563
Appendix A 564
A.l. Network implementation of the explicit system 564
A.2. Network implementation of the implicit system 566
Acknowledgment 568
References 568
Chapter 26
The Neuropsychology of Perceptual Category Learning
W. TODD MADDOX and J. VINCENT FDLOTEO
Abstract 574
1. Introduction 575
2. Competition between verbal and implicit Systems (COVIS) 575
3. Testing a priori Predictions of COVIS 578
4. Perceptual category learning in neurological patients 581
4.1. Nonlinear information integration category learning in amnesia 582
4.2. Nonlinear information integration category learning in striatal damaged patients 585
4.3. Rule based category learning in PD 587
4.4. Further study of information integration category learning in PD 591
5. General discussion 595
References 597
Chapter 27
Neural Regions Associated with Categorical Speech Perception and Production
SUSAN M. RAVIZZA
Abstract 601
1. Introduction 602
2. Evidence for categorical Speech processing 602
3. Prefrontal regions and motor speech categories 605
4. Temporal parietal regions and acoustic speech categories 609
5. Cerebellar contributions to categorical production and perception 611
6. Concluding remarks 612
References 613
PART 6 CATEGORIES IN PERCEPTION AND INFERENCE
Chapter 28
Situated Conceptualization
LAWRENCE W. BARSALOU
Abstract 620
1. Introduction 621
1.1 Conceptual Systems 621
1.2 Semantic memory 621
2. Grounding the conceptual System in the modalities 622
2.1. Modal reenactments of perception, action, and introspection 623
2.2. Simulators and simulations 624
2.3. Situated conceptualizations 626
2.4. Inference via pattern completion 628
3. Empirical evidence 629
3.1. Behavioral evidence for a modal nonmodular conceptual System 629
3.2. Neural evidence for a modal nonmodular conceptual System 637
3.3. Evidence for situated conceptualizations 639
4. Conclusion 644
4.1. Important issues for future research 645
Acknowledgment 647
References 647
Chapter 29
Perceptual and Semantic Reorganization during Category Learning
ROBERT L. GOLDSTONE, BRIAN J. ROGOSKY, RACHEL PEVTZOW
and MARK BLAIR
Abstract 652
1. Introduction 653
2. Concept learning and perception 653
2.1. Object segmentation 654
2.2. Experiment 1 655
2.3. Experiment 2 657
2.4. Conclusions on perceptual reorganization 662
3. Semantic reorganization during category learning 664
3.1. Integral versus separable dimensions 664
3.2. Experiment 3 665
3.3. Experiment 4 669
4. Conclusions on semantic reorganization 671
5. Integrating perceptual and semantic reorganization 671
5.1. Characterizing psychological features 672
5.2. Characterizing featural change 673
5.3. Prospects for synthesizing perceptual and semantic reorganization 675
Acknowledgments 676
References 676
Chapter 30
The Return of Concept Empiricism
JESSE J. PRINZ
Abstract 679
« A1A
1. Introduction 680
2. Concept empiricism 680
2.1. Representing and doing: Two faces of concepts 680
2.2. Variable mechanisms 684
2.3. Perceptual vehicles 686
2.4. Innateness 688
2.5. Summary 691
3. The abstract ideas objections 692
References 694
PART 7 GROUNDING, RECOGNITION, AND REASONING IN
CATEGORIZATION
Chapter 31
Categorization, Reasoning, and Memory from a Neo logical Point of View
SERGE ROBERT
Abstract 700
1. Introduction 701
2. Order, Information, and Categories 701
3. Inferences, Arguments, and Information 701
4. Logical and Creative Arguments 703
5. Types of Creative Arguments 703
6. Two Rather Incompatible Views in Cognitive Science 705
7. Experiments on Memory and Logical Competence 706
8. Logical Weakness and Classification of Errors 709
9. A New Theory of Logical Error and Logical Competence 710
10. The Cognitive Functions of Logic 711
11. Corrective Inferences and Cognitive Progress 713
12. The Fundamental Cognitive Function of Logical Reasoning 715
13. The Mind as a Dynamic System: Inference and Memory 715
14. General Conclusions: Categorization, Reasoning, and Memory 716
References 717
Chapter 32
Approaches to Grounding Symbols in Perceptual and Sensorimotor Categories
ANGELO CANGELOSI
Abstract 719
1. Cognitive symbol grounding 720
1.1. The symbol grounding problem 720
1.2. Grounding Symbols in cognition 721
2. Linking vision and language: connectionist approaches to
category learning and symbol grounding 724
2.1. Connectionist modeling of category learning and naming 724
2.2. Connectionist modeling of symbol grounding transfer 727
3. Linking Vision, action and language: embodied approaches to
language learning and evolution 729
3.1. Grounding symbols in simulated agents: The symbolic theft hypothesis 729
3.2. The emergence of language in robots 731
4. Discussion and conclusion 733
References 735
Chapter 33
Embodied Categorization
PIERRE POIRIER, BENOIT HARDY VALLEE and
JEAN FREDERIC DEPASQUALE
Abstract 740
1. Introduction: Embodied categorization 741
2. Purely reactive categorizers 743
2.1. The perceptual aliasing problem [Whitehead and Ballard (1991)] 744
2.2. Type I versus II problems [Clark and Thornton (1997)] 744
3. Reactive categorizers that learn 747
4. Representing categorizers 749
5. Emulating and simulating categorizers 752
5.1. Emulating categorizers 753
5.2. Simulating categorizers 755
6. Analogizing categorizers 759
7. Linguistic categorizers 761
8. Conclusion 761
References 762
Chapter 34
Categorization of Objects, Scenes, and Faces through Time
ERIC McCABE, CAROLINE BLAIS and FREDERIC GOSSELBSf
Abstract 768
1. A model of categorization 769
2. Basic level literature 772
3. Discrete processing cycles 773
3.1. A Bubbles primer 773
3.2. Fossilized discrete processing cycles 775
3.3. What can temporal bubbles reveal about a SLIP categorizer? 777
4. The need for flexibility and a paradox 778
4.1. Limited processing capacity 778
4.2. The need for flexibility 779
4.3. Back to the paradox 780
5. Categorization as an iterative process 780
5.1. Compulsory feedforward processing sweeps 781
5.2. Flexible iterative processing sweeps 782
6. General discussion 786
References 788
Chapter 35
Adaptive Categorization and Neural Networks
ROBERT PROULX and SEBASTIEN HELIE
Abstract 794
1. The problem of divergence 798
2. The solution: dual Hebbian/anti Hebbian learning 799
2.1. Stabilization 800
2.2. Oscillation 801
2.3. Linearity 801
2.4. Additional properties of the learning rule 801
3. The Eidos model 802
4. The letter classification task 803
4.1. Methodology 803
4.2. Results 804
5. The problem of convergence 806
6. The solution: Unlearning 808
7. The letter classification task revisited 809
7.1. Methodology 809
7.2. Results 809
8. Current trends: Elimination of spurious attractors 812
9. Conclusion 813
References 814
Chapter 36
A Grounded Mind in a Robotic Body
STEVAN HARNAD 817
PART 8 MACHINE CATEGORY LEARNING
Chapter 37
Concept Learning and Nonmonotonic Reasoning
PETER GÄRDENFORS
Abstract 824
1. The role of concepts 825
2. Three kinds of cognitive representations 825
3. Learning in symbolic Systems 826
4. Learning in connectionist Systems 827
5. Conceptual Spaces as a representational framework 827
6. The origin of quality dimensions 829
7. Properties and concepts 831
8. Prototypes and conceptual Spaces 832
9. Learning in conceptual Spaces 834
10. The role of similarity in learning 836
11. Nonmonotonic aspects of concepts 838
11.1. Change from general category to subordinate 839
11.2. Context effects 840
12. Conclusion 841
References 842
Chapter 38
Categorization in Symbolic Data Analysis
EDWIN DIDAY
Abstract 846
1. Introduction 847
2. Categories, concepts, and symbolic data 848
2.1. From individuals to concepts 848
2.2. Categories in a database 849
2.3. From categories to concepts: reification of a category in a concept 849
2.4. Sources of symbolic data 851
3. Symbolic data tables and their background knowledge, concepts,
and categories 852
3.1. Symbolic data tables 852
3.2. Building a symbolic data table by reification of categories in concepts 852
3.3. Description of concepts when the individuals are described by fuzzy data 853
3.4. Adding conceptual variables, joining concepts, and the DB2SO
moduleof SODAS 854
4. Modeling concepts by symbolic objects, with certain
philosophical aspects 855
4.1. Kinds of concepts and intuitive introduction of symbolic objects 855
4.2. Modeling concepts with four Spaces: individuals, concepts,
descriptions, and symbolic objects 855
4.3. Extent of concepts and symbolic objects 856
4.4. Syntax of symbolic objects in the case of assertions 858
4.5. Extent of a symbolic object 858
4.6. Concepts: Four approaches 858
5. Tools for symbolic objects 859
5.1. Order between symbolic objects 859
5.2. Finding a unique description for a concept: T norm of descriptive generalization 859
5.3. Finding several descriptions for a concept 860
5.4. Dissimilarities between concepts 861
5.5. Finding prototypes from a concept 861
6. Underlying structures of symbolic objects 861
6.1. A generalized conceptual lattice 861
6.2. Mathematical framework of a symbolic data analysis 863
7. Steps and tools for Symbolic Data Analysis 863
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7.1. Main Steps 863
7.2. Descriptive SDA in SODAS 864
8. Overview of SODAS 865
8.1. Some advantages of the use of concepts modeled by symbolic objects 865
8.2. Overview of SODAS Software 865
9. Final remarks 865
References 866
Chapter 39
Category Formation in Self organizing Embodied Agents
STEFANO NOLFI
Abstract 869
1. Introduction 870
2. Themethod 870
3. Categories emerging from the interaction between
the agent and the environment 871
3.1. Finding and remaining in favorable environmental areas 871
3.2. Discriminating objects with different shapes on the basis of tactile information 873
3.3. Behavior emerging from the dynamic interaction between the agent and its environment 876
4. Action mediated sensory states 878
4.1. Discriminating larger and smaller cylindrical objects 879
4.2. Navigating toward a target area of the environment 881
5. Integrating sensorimotor information over time and the emergence of
complex internal categories 883
5.1. The self localization problem 884
6. Conclusions 887
Acknowledgments 888
References 888
Chapter 40
An Information based Discussion of Vagueness:
Six Scenarios Leading to Vagueness
DIDIER DUBOIS and HENRI PRADE,
FRANCESC ESTEVA and LLUIS GODO
Abstract 892
1. Introduction 893
2. The information framework 894
3. Classical vs. gradual properties 895
3.1. Graduality and partial preorderings 895
3.2. Membership functions as total preorders 896
3.3. Fuzzy sets and similarity to prototypes 897
3.4. Set theoretic operations 897
3.5. Graduality is a useful form of vagueness 898
4. Precisely defined vs. poorly defined properties 899
4.1. Classification ambiguity 900
4.2. Vagueness as limited perception 900
4.3. Supervaluations 901
4.4. Ill known partial membership 901
5. Refining precisely defined properties using closeness relations 901
6. Single agent vs. multiple agents 902
7. Ill known attribute values and twofold sets 904
8. Approximately described sets 905
9. Concluding remarks 906
References 907
PART 9 DATA MINING FOR CATEGORIES AND ONTOLOGIES
Chapter 41
A Smooth Introduction to Symbolic Methods for Knowledge Discovery
AMEDEO NAPOLI
Abstract 914
1. Introduction 915
2. Methods for KDD 916
2.1. An introductory example 916
2.2. Data mining methods 917
3. Lattice based classification 918
4. Frequent itemset search and association rule extraction 920
4.1. Frequent itemset search 921
4.2. Association rule extraction 923
5. Applications 923
5.1. Mining chemical reaction database 924
5.2. An experiment in biology 927
5.3. An introduction to Web mining 928
6. Discussion 930
7. Conclusion 930
References 931
Chapter 42
Genre Specific Text Mining and Extensional Inductive Concept Recognition:
A Pseudocognitive Approach
YVES KODRATOFF
Abstract 936
1. Introduction and definition of text mining (TM) 937
1.1. Text mining 937
1.2. Our approach 938
2. Text retrieval 939
J AAV
3. Standardization 940
4. Grammatical tagging 940
4.1. Why expert rules at the tagging stage? 941
4.2. A tagging language 942
4.3. Our approach to grammatical tagging 943
4.4. Automatic learning of new tagging rules 943
5. Terminology 944
6. Concept recognition in texts 944
6.1. Polysemy 945
6.2. General versus local collocations 945
6.3. Terms and collocations 945
6.4. ACT as a friendly interface helping the expert 946
6.5. ACT as an inductive program 947
6.6. Validation 951
7. Conclusion 951
Acknowledgments 952
References 953
Chapter 43
Classification and Categorization in Computer Assisted
Reading and Text Analysis
JEAN GUY MEUNffiR, DOMINIC FOREST and ISMAIL BISKRI
Abstract 956
1. Introduction 957
1.1. CARAT: General presentation 957
1.2. Difficulties with the technology 958
1.3. The nature of reading and analyzing a text 959
2. Definitions of classification and categorization for CARAT 961
3. Text classification and categorization 962
3.1. Text classification 962
3.2. Text categorization 962
3.3. Computer text classification and categorization 963
4. Methodology for text classifying and categorizing 963
4.1. Steps 1, 2, and 3: From a text to a matrix 964
4.2. Steps 4 and 5 967
4.3. Step 6: Navigation 968
4.4. Step 7: Evaluation 968
5. Applications in CARAT 969
5.1. Thematic analysis 969
5.2. Categoricalexplorationofphilosophical texts 970
5.3. Content analysis 972
6. The Computer design: SATIM 974
6.1. The Workshop 974
6.2. The laboratory 975
6.3. Applications 975
7. Conclusion 976
References 976
Chapter 44
Graph Matching, System Design and Knowledge Modeling
GUY W. MINEAU
Abstract 979
1. Introduction 980
2. Knowledge represented as graph structures 982
3. Learning heuristic knowledge 984
4. Viability conditions 985
5. The complexity of learning 986
6. Categorization of knowledge in layers 988
7. Conclusion 989
References 989
PART 10 THE NATURALIZATION OF CATEGORIES
Chapter 45
Nominalism and the Theory of Concepts
CLAUDE PANACCIO
Abstract 993
1. Nominalism 994
2. Ockham s cleaver 995
3. Motivations 999
4. Nominalistic constraints for the theory of concepts 1001
4.1. Represented things as Singular 1002
4.2. Representations as Singular 1004
References 1006
Chapter 46
Why do We Think Racially?
EDOUARD MACHERY, LUC FAUCHER
Abstract 1010
1. Introduction 1011
2. Is racialism a mere social construct? 1012
2.1. Racial skepticism 1012
2.2. Races are interactive kinds 1013
2.3. Races are transient kinds 1013
2.4. Merits and problems 1015
3. Is racialism a by product of a human kind module? 1016
laoie oj Contents xxvii
3.1. The nature of racialism 1016
3.2. The human kind module 1017
3.3. Empirical evidence 1017
3.4. Merits and problems 1019
4. Are races mere coalitions? 1021
4.1. Races and coalitions 1021
4.2. Empirical evidence 1021
4.3. Merits and problems 1022
5. Is racialism a by product of an evolved ethnic cognitive System? 1024
5.1. Ethnies are not mere coalitions 1024
5.2. An adaptive scenario: Ethnic cognition and the exaptation of human folk biology 1025
5.3. Empirical evidence 1026
5.4. Merits and problems 1027
6. Conclusion 1029
References 1031
Chapter 47
Neurosemantics and Categories
CHRIS ELIASMITH
Abstract 1036
1. Introduction 1037
1.1. Why neuro ? 1037
1.2. The explanandum 1039
2. Mental representations as neural codes 1040
2.1. Representations 1040
2.2. Transformation 1041
2.3. A representational hierarchy 1042
3. The meaning of neural representations: Neurosemantics 1043
3.1. The representation relation 1043
3.2. A neurosemantic theory 1044
3.3. Discussion 1049
4. Misrepresentation 1050
5. Conclusion 1052
References 1052
Chapter 48
Conceptual Analysis and Philosophical Naturalism
ELISABETTA LALUMERA
Abstract 1055
1. Introduction 1056
2. What is intuitive about conceptual analysis? 1057
3. Cognitive Privileges, metaphysical Privileges, and the Transparency Thesis 1058
4. Against Privileges 1059
5. The inward approach 1061
6. Conceptual truths or truths about concepts? 1062
7. The outward approach 1064
8. Bachelors are unmarried men is about facts 1065
9. Explaining away the illusion 1067
10. A mixedbag 1068
11. Conclusion 1070
References 1070
Chapter 49
Crisis! What Crisis? 1073
PIERRE POIRIER
Index 1081
|
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| spellingShingle | Handbook of categorization in cognitive science Categorieën (taalkunde) gtt Catégories (Philosophie) rasuqam Catégorisation (Psychologie) Catégorisation rasuqam Processus cognitif rasuqam Science cognitive rasuqam Sciences cognitives Linguistik Categorization (Psychology) Cognition Cognitive Science Cognitive science Linguistics Kategorisierung (DE-588)4163445-7 gnd Kognitionswissenschaft (DE-588)4193780-6 gnd Kognitive Psychologie (DE-588)4073586-2 gnd Kognitive Linguistik (DE-588)4246269-1 gnd |
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| title | Handbook of categorization in cognitive science |
| title_auth | Handbook of categorization in cognitive science |
| title_exact_search | Handbook of categorization in cognitive science |
| title_full | Handbook of categorization in cognitive science ed. by Henri Cohen ... |
| title_fullStr | Handbook of categorization in cognitive science ed. by Henri Cohen ... |
| title_full_unstemmed | Handbook of categorization in cognitive science ed. by Henri Cohen ... |
| title_short | Handbook of categorization in cognitive science |
| title_sort | handbook of categorization in cognitive science |
| topic | Categorieën (taalkunde) gtt Catégories (Philosophie) rasuqam Catégorisation (Psychologie) Catégorisation rasuqam Processus cognitif rasuqam Science cognitive rasuqam Sciences cognitives Linguistik Categorization (Psychology) Cognition Cognitive Science Cognitive science Linguistics Kategorisierung (DE-588)4163445-7 gnd Kognitionswissenschaft (DE-588)4193780-6 gnd Kognitive Psychologie (DE-588)4073586-2 gnd Kognitive Linguistik (DE-588)4246269-1 gnd |
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