Provides valuable insight into the progress and direction of development of the World Wide Web and its likely future applications in science and business. Reviews the prospects for the Web to develop intelligent services (such as online businesses, games, purchases, new search capabilities, and accessibility to trustworthy information). Offers a view for thinking about thinking on the Web. The companion website offers access to supplemental text, specialized information, additional examples, demos, tools reference material, and advanced applications.

H. Peter Alesso is an innovator with twenty years' research experience at Lawrence Livermore National Laboratory (LLNL). As Engineering Group Leader at LLNL, he led a team of computer scientists and engineers in innovative applications across a wide range of supercomputers, workstations, and networks. He has published several software titles and scientific journal and conference articles, and is the author or coauthor of five books.

Craig F. Smith, PhD, is a Fellow of the American Association for the Advancement of Science (AAAS) with over thirty years' experience in research and development for applications of advanced technologies. He currently serves as the Lawrence Livermore Chair Professor at the Naval Postgraduate School in Monterey, California. He is the coauthor of four books.

Foreword	p. xiii
Preface	p. xv
Acknowledgments	p. xxi
Who This Book Is For	p. xxiii
The Organization of This Book	p. xxv
Associated Resources	p. xxvii
What is Web Intelligence?	p. 1
Empowering the Information Age	p. 3
Overview	p. 3
Thinking and Intelligent Web Applications	p. 4
The Information Age	p. 6
The World Wide Web	p. 11
Limitations of Today's Web	p. 14
The Next-Generation Web	p. 15
Why Intelligent Ubiquitous Devices Improve Productivity	p. 15
Conclusion	p. 17
Exercises	p. 17
Thinking about Thinking	p. 19
Godel: What Is Decidable?	p. 21
Overview	p. 21
Philosophical and Mathematical Logic	p. 22
Kurt Godel	p. 27
Knowledge Representation	p. 33
Computational Logic	p. 34
Artificial Intelligence	p. 35
Web Architecture and Business Logic	p. 36
The Semantic Web	p. 36
Conclusion	p. 40
Exercises	p. 40
Truth and Beauty	p. 43
Turing: What Is Machine Intelligence?	p. 45
Overview	p. 45
What Is Machine Intelligence?	p. 45
Alan Turing	p. 46
Turing's Test and the Loebner Prize	p. 49
John Searle's Chinese Room	p. 49
Artificial Intelligence	p. 49
Machine Intelligence	p. 51
Semantic Networks and Frames	p. 51
Reasoning with Semantic Networks	p. 52
Computational Complexity	p. 53
Description Logic (DL)	p. 54
Ontology	p. 55
Inference Engines	p. 56
Software Agents	p. 56
Adaptive Software	p. 57
Limitations and Capabilities	p. 57
Conclusion	p. 58
Exercises	p. 58
Computing Machines	p. 60
Berners-Lee: What Is Solvable?	p. 63
Overview	p. 63
The World Wide Web	p. 64
Time Berners-Lee	p. 64
The Semantic Web Roadmap	p. 68
Logic on the Semantic Web	p. 75
Semantic Web Capabilities and Limitations	p. 77
Conclusion	p. 77
Exercises	p. 78
Turing's Test	p. 80
Web Ontology and Logic	p. 83
Resource Description Framework (RDF)	p. 85
Overview	p. 85
HTML Language	p. 86
XML Language	p. 86
RDF Language	p. 88
Basic Elements	p. 92
RDF Schema	p. 97
XQuery: XML Query Language	p. 104
Conclusion	p. 105
Exercises	p. 106
The Chinese Room	p. 108
Web Ontology Language (OWL)	p. 111
Overview	p. 111
Ontology Language	p. 112
Ontology Language Requirements	p. 113
Compatibility of OWL and RDF/RDFS	p. 114
The OWL Language	p. 116
Basic Elements	p. 117
OWL Example: Compute Ontology	p. 121
Ontology Example: Birthplace	p. 123
Applying OWL	p. 124
OWL Capabilities and Limitations	p. 125
Conclusion	p. 126
Exercises	p. 126
Machines and Brains	p. 128
Ontology Engineering	p. 131
Overview	p. 131
Ontology Engineering	p. 131
Constructing Ontology	p. 133
Ontology Development Tools	p. 134
Ontology "Spot" Example	p. 135
Ontology Methods	p. 137
Ontology Sharing and Merging	p. 139
Ontology Libraries	p. 140
Ontology Matching	p. 140
Ontology Mapping	p. 142
Ontology Mapping Tools	p. 143
Conclusion	p. 143
Exercises	p. 143
Machines and Meaning	p. 145
Logic, Rules, and Inference	p. 149
Overview	p. 149
Logic and Inference	p. 150
Monotonic and Nonmonotonic Rules	p. 154
Description Logic	p. 154
Inference Engines	p. 155
RDF Inference Engine	p. 159
Conclusion	p. 162
Exercises	p. 163
Machines and Rules	p. 165
Semantic Web Rule Language (SWRL)	p. 169
Overview	p. 169
Rule Systems	p. 170
Rule Languages	p. 171
Semantic Web Rule Language (SWRL)	p. 171
Conclusion	p. 173
Exercise	p. 174
Machines and Language	p. 175
Semantic Web Applications	p. 177
Overview	p. 177
Semantic Web Applications	p. 177
Semantic Web Services	p. 179
Semantic Search	p. 180
e-Learning	p. 180
Semantic Bioinformatics	p. 182
Enterprise Application Integration	p. 182
Knowledge Base	p. 184
Conclusion	p. 185
Exercise	p. 185
Distributed Intelligence	p. 186
Web Ontology Language for Services (OWL-S)	p. 189
Overview	p. 189
XML-Based Web Services	p. 190
Next-Generation Web Services	p. 190
Creating an OWL-S Ontology for Web Services	p. 201
Conclusion	p. 202
Exercises	p. 202
The Semantic Web	p. 203
Semantic Search Technology	p. 205
Overview	p. 205
Search Engines	p. 206
Semantic Search	p. 208
Semantic Search Technology	p. 209
Web Search Agents	p. 212
Semantic Methods	p. 214
Latent Semantic Index Search	p. 214
TAP	p. 217
Swoogle	p. 218
Conclusion	p. 220
Exercises	p. 220
The Halting Problem	p. 221
Semantic Patterns and Adaptive Software	p. 223
Overview	p. 223
Patterns in Software Design	p. 223
Pattern Frame	p. 224
Semantic Patterns	p. 225
Self-Organizing and Adaptive Software	p. 227
Conclusion	p. 229
Exercise	p. 230
The Semantic Web and Rules	p. 231
Semantic Tools	p. 233
Overview	p. 233
Semantic Tools	p. 233
Semantic Web Services Tools	p. 239
Conclusion	p. 241
Exercise	p. 241
The Semantic Web and Language	p. 242
Challenges and Opportunities	p. 245
Overview	p. 245
Semantic Doubts	p. 246
Semantic Opportunities	p. 247
Challenges	p. 248
Balancing Proprietary and Open Standards	p. 250
Conclusion	p. 251
The Semantic Web and Zeno's Paradox	p. 253
Bibliography	p. 255
Glossary	p. 271
Acronyms	p. 287
Index	p. 289
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