상세정보

CONTENTS
Preface = xi
PART Ⅰ Overview
 Chapter 1 Introduction = 3
  1.1 Task : Processing Script-Based Narratives = 3
  1.2 Motivation and Goals = 5
  1.3 Approach = 7
  1.4 Guide to the Reader = 10
 Chapter 2 Background = 13
  2.1 Scripts = 13
  2.2 Parallel Distributed Processing = 17
 Chapter 3 overview of DISCERN = 23
  3.1 System Architecture = 23
  3.2 I/O Example = 28
  3.3 Training and Performance = 30
PART Ⅱ  Processing Mechanisms
 Chapter 4 Backpropagation Networks = 37
  4.1 The Basic Iden = 37
  4.2 Detatils of the Algorithm = 39
  4.3 Variations = 41
  4.4 Application Considerations = 44
 Chapter 5 Developing Representations in FGREP Modules = 47
  5.1 The Basic FGREP Mechanism = 47
  5.2 Subtask : Assigning Case Roles to Sentence constituents = 50
  5.3 Properties of FGREP Representations = 53
  5.4 Cloning Synonymous Word Instances : The ID+content Technique = 69
  5.5 Processing Sequential Input and Output : The Recurrent FGREP Module = 77
  5.6 Limitations of FGREP = 82
 Chapter 6 Building from FGREP Modules = 85
  6.1 Performance Phase = 85
  6.2 Training Phase = 85
  6.3 Processing Modules in DISCERN = 90
  6.4 Limitations of the Modular FGREP Approach = 99
PART Ⅲ Memory Mechanisms
 Chapter 7 Self-Organizing Feature Maps = 105
  7.1 Topological Feature Maps = 105
  7.2 Self-Organization = 109
  7.3 Biological Feature Maps = 114
  7.4 Feature Maps as Memory Models = 117
 Chapter 8 Episodic Memory Organization : Hierarchical Feature Maps = 119
  8.1 The General Hierarchical Feature Map Architecture = 119
  8.2 Hierarchical Feature Maps in DISCERN = 122
  8.3 Memory Organization Properties = 133
  8.4 Self-Organization Properties = 137
 Chapter 9 Episodic Memory Storage and Retrieval : Trace Feature Maps = 141
  9.1 A General Model of Trace Feature Maps = 141
  9.2 Trace Feature Maps in DISCERN = 150
  9.3 Storage and Retrieval from Episodic Memory = 155
  9.4 Modeling Human Memory : Interpretation and Limitations = 159
 Chapter 10 Lexicon = 163
  10.1 Overview of the Architecture = 163
  10.2 Representation of Lexical Symbols = 165
  10.3 Properties of the Lexicon Model = 165
  10.4 The Lexicon in DISCERN = 178
  10.5 Modeling the Human Lexical System = 185
  10.6 Limitations = 190
PART Ⅳ Evaluation
 Chapter 11 Behavior of the Complete Model = 197
  11.1 Connecting the Modules = 197
  11.2 Example Run = 204
  11.3 Cleaning Up Errors = 219
  11.4 Error Behavior = 224
  11.5 Conclusion = 233
 Chapter 12 Discussion = 235
  12.1 DISCERN as a Physical Model = 235
  12.2 DISCERN as a Cognitive Model = 237
  12.3 DISCERN as a Developmental Model = 239
  12.4 Making Use of Modularity = 242
  12.5 The Role of the Central Lexicon = 245
  12.6 Robustness and stability = 247
  12.7 Generalization in Question Answering = 248
  12.8 Exceptions and Novel Situations = 249
 Chapter 13 Comparison to Related Work = 251
  13.1 Symbolic Models of Natural Language Processing = 251
  13.2 parallel Distributed Models of Natural Language Processing = 253
  13.3 Localist Models = 261
  13.4 Hybrid Models = 264
  13.5 Models of the Lexicon = 272
  13.6 Models of Episodic Memory = 275
  13.7 Issues in Subsymbolic Cognitive Modeling = 279
 Chapter 14 Extensions and Future work = 301
  14.1 Sentence Processing = 301
  14.2 Script Processing = 304
  14.3 Concept Representations = 307
  14.4 Lexicon = 309
  14.5 Episodic Memory = 313
  14.6 Question Answering = 319
  14.7 Parallel Distributed Control = 320
  14.8 Processing Multiple Languages = 322
  14.9 Representing and Learning Knowledge Structures = 326
 Chapter 15 Conclusions = 331
  15.1 Summary of the DISCERN Model = 331
  15.2 Conclusion = 335
Appendix A Story Data = 337
Appendix B Implementation Details = 343
Appendix C Instructions for Obtaining the DISCERN Software = 345
Bibliography = 347
Author Index = 375
Subject Index = 381