Knowledge Processing and Applied Artificial Intelligence (eBook)

Soumitra Dutta (Autor)

eBook Download: PDF

2014 | 1. Auflage
368 Seiten
Elsevier Science (Verlag)
978-1-4831-8392-3 (ISBN)

Infos

Knowledge Processing and Applied Artificial Intelligence discusses the business potential of knowledge processing and examines the aspects of applied artificial intelligence technology. The book is comprised of nine chapters that are organized into five parts. The text first covers knowledge processing and applied artificial intelligence, and then proceeds to tackling the techniques for acquiring, representing, and reasoning with knowledge. The next part deals with the process of creating and implementing strategically advantageous knowledge-based system applications. The fourth part covers intelligent interfaces, while the last part details alternative approaches to knowledge processing. The book will be of great use to students and professionals of computer or business related disciplines.

Soumitra Dutta is the eleventh dean and professor of management and organizations in the Samuel Curtis Johnson Graduate School of Management at Cornell University. He most recently served as the Roland Berger Chaired Professor of Business and Technology. Dutta is an authority on the impact of new technology on the business world, especially social media and social networking, and on strategies for driving growth and innovation by embracing the digital economy. He is the co-editor and author respectively of two influential reports in technology and innovation -- the Global Information Technology Report (co-published with the World Economic Forum) and the Global Innovation Index (to be co-published with the World Intellectual Property Organization). Both reports have been used by several governments around the world in assessing and planning their technology and innovation policies.

Inhalt

Front Cover 1
Knowledge Processing and Applied Artificial Intelligence 2
Copyright Page 3
Table of Contents 6
Dedication 4
Preface 12
Acknowledgements 14
Part I 18
Chapter 1. knowledge processing and applied artificial intelligence 20
The evolution of computing in business 21
The rise of knowledge processing 22
The origins of knowledge processing 23
Philosophy 24
Mathematics 25
Computing 26
The development of the field of artificial intelligence 27
A shift in focus 28
The evolving sub-fields 28
Governmental funding 30
The nature of intelligence 31
Applied artificial intelligence 32
Knowledge processing and applied artificial intelligence 32
The commercialization of applied artificial intelligence 34
Consolidation and growth 35
The commercial market 36
Moving from data processing to knowledge processing 37
Structure and organization of book 38
Summary 40
Bibliography and suggested readings 41
Notes 42
Part II 46
Chapter 2. Knowledge-based systems and the acquisition of knowledge 48
Digital Equipment Corporation 49
American Express 49
Campbell Soup 50
Structure of knowledge-based systems 51
The process of building knowledge-based systems 53
Expert systems and knowledge-based systems 54
Epistemology and knowledge-based systems 54
The definition of knowledge 56
The computer configuration problem 56
The dimensions of knowledge 57
Stages of knowledge 59
Knowledge in a knowledge-based system 60
Knowledge acquisition 60
Knowledge engineer-guided knowledge acquisition 61
Planning the knowledge acquisition process 62
Automated tools for knowledge acquisition 65
Induction 65
Steps after knowledge acquisition 67
Summary 68
Bibliography and suggested readings 70
Notes 71
Chapter 3. Representing and reasoning with knowledge 74
Knowledge representation using rules 75
Complex rules and structured rule-based systems 76
Forward chaining 77
Backward chaining 79
A comparison of backward and forward chaining 79
Meta-knowledge in rule-based reasoning 81
Rule-based reasoning under uncertainty 82
Prolog: a simple rule-based system 84
The inference procedure of Prolog 84
Benefits and limitations of rule-based reasoning 90
Networked representations of knowledge 91
Semantic networks 92
Frame hierarchies 93
Structure of objects 94
Behaviors of objects 97
Communication between objects 99
Comparing frame hierarchies and rules 100
Alternative approaches to knowledge representation 101
Blackboard systems 101
Case-based reasoning 103
Summary 105
Bibliography and suggested readings 106
Notes 107
Part III 110
Chapter 4. Creating knowledge-based systems 112
Creating rule-based systems 113
Problem description 113
Problem decomposition 114
Initial prototype 115
Incremental evolution 116
Customization 119
Structured rule-based systems 119
Creating hybrid knowledge-based systems 121
Problem description 121
Frame hierarchy identification 122
Structure and behavior identification 123
Prototyping and incremental evolution 125
Customization 128
Customizing the user-interface 128
Interfaces to databases 131
Tools for building knowledge-based systems 133
Types of shell tools 134
Hardware platforms for shell tools 135
Guidelines for the selection of shell tools 136
Commercial market for knowledge-based products 137
The database and knowledge-based product markets 138
Summary 140
Bibliography and suggested readings 142
Notes 143
Chapter 5. Strategic and organizational issues in knowledge processing 146
Levels of organizational knowledge 147
Managing knowledge in organizations 147
Knowledge-based systems and the management of knowledge 149
Applications of knowledge-based systems in organizations 152
Organizational benefits 158
Organizational hazards 160
Impact on industry structures 161
Managing the development process in organizations 162
Choosing a corporate strategy for knowledge processing 162
Factors affecting the knowledge processing strategy 166
Identification of potential knowledge-based applications 167
Cost-benefit analyses of potential applications 168
Determining feasibility of applications 169
Creation of knowledge-based applications 170
Deployment of applications 172
Maintenance of applications 173
Summary 175
Bibliography and suggested readings 177
Notes 178
Part IV 180
Chapter 6. Natural language processing 182
The Securities and Exchange Commission 182
Siemens-Nixdorf 183
Components of natural language processing 184
The nature of understanding 185
Ambiguity in natural language understanding 186
Approaches to natural language understanding 187
Syntax and semantics 190
Knowledge-based 193
Understanding multiple sentences and dialogs 196
Machine translation 197
Approaches to machine translation 197
Machine translation in industry 200
Evaluating natural language interfaces 201
Commercial tools for natural language processing 202
Applications of natural language processing 203
The business impact of natural language processing 207
Summary 208
Bibliography and suggested readings 210
Notes 211
Chapter 7. Image and speech processing 214
Computer vision 215
Biological roots 215
Computational requirements 216
Problems and ambiguities 217
Information processing in machine vision 220
Signal processing 221
Image processing 225
Image understanding 227
Commercial applications of machine vision 229
Document image processing 233
Diagnostic heart imagery 236
Microfossil identification 237
Speech processing 238
Speech recognition 240
Speech understanding 241
The business impact of image and speech processing 244
Summary 245
Bibliography and suggested readings 246
Notes 247
Part V 250
Chapter 8. Approximate reasoning using fuzzy logic 252
Hitachi: the Sendai subway control system 252
Yamaichi Securities: intelligent trading programs 253
Matshushita: intelligent washing machines 254
Rockwell: modelling stress on wings 254
Development of fuzzy logic 255
Fundamentals of fuzzy logic technology 256
Reasoning procedures 259
Comparing fuzzy and conventional rules 263
Case studies of fuzzy logic applications 264
Sendai subway control 268
Commercial activities in fuzzy logic 270
Asia 271
America 273
Europe 274
The business impacts of fuzzy logic applications 275
Summary 278
Bibliography and suggested readings 279
Notes 280
Chapter 9. Connectionist modelling of intelligence 282
The connectionist approach 283
History of connectionism 283
Neural networks 284
Problem types tackled by neural networks 285
Types of neural networks 286
Selected neural network architectures 287
The Hopfield net 292
Kohonen's self-organizing feature maps 292
Designing applications using neural networks 293
Domain and problem characteristics 293
Designing the network 294
Training and testing the network 296
Maintaining and integrating applications 298
Commercial tools 299
Case study: using neural networks for bond rating 299
The problem of bond rating 301
Results 304
Applications of neural networks 305
Strengths and limitations of connectionist models 308
The future of symbolic and connectionist approaches 310
Summary 311
Bibliography and suggested readings 313
Notes 314
Appendix 1: Commercial applications of knowledge-based systems 318
Expert auditing of airline passenger tickets 319
Inspector: monitoring foreign exchange trading 
320 
Nynex Max: troubleshooting telephones 
322 
Lending advisor: credit analysis 
323 
Agatha: diagnosing personal computer boards 
326 
Qdes: quality design for steel products 
327 
OHCS: hydraulic circuit design 
329 
MOCA: airline maintenance scheduling 
330 
Ecapp: intelligent process planning 
332 
Bibliography and suggested readings 334
Notes 335
Appendix 2: Commercial vendors of knowledge-based products 338
Bibliography and suggested readings 355
Notes 356
Appendix 3: Commercial applications of neural networks 358
Airline 359
Defence 359
Financial services 360
Government 361
Healthcare 361
Marketing 362
Manufacturing 362
Space 364
Bibliography and suggested readings 365
Notes 366
Index 367

Produkt-Details

• Erscheint lt. Verlag: 16.5.2014
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Technik ► Bauwesen
• ISBN-10: 1-4831-8392-0 / 1483183920
• ISBN-13: 978-1-4831-8392-3 / 9781483183923