Knowledge Processing and Applied Artificial Intelligence

Preface Acknowledgments List Of Abbreviations Part II Chapter 1 — Knowledge Processing and Applied Artificial Intelligence The Evolution of Computing in Business The Rise of Knowledge Processing The Origins of Knowledge Processing Philosophy Mathematics Computing The Development of the Field of Artificial Intelligence A Shift in Focus The Evolving Sub-Fields Governmental Funding The Nature of Intelligence Applied Artificial Intelligence Knowledge Processing and Applied Artificial Intelligence The Commercialization of Applied Artificial Intelligence Consolidation and Growth The Commercial Market Moving From Data Processing to Knowledge Processing Structure and Organization of Book Summary Bibliography and Suggested Readings NotesPart II — Acquiring, Representing, and Reasoning with Knowledge Chapter 2 — Knowledge-Based Systems and the Acquisition of Knowledge Digital Equipment Corporation American Express Campbell Soup Structure of Knowledge-Based Systems The Process of Building Knowledge-Based Systems Expert Systems and Knowledge-Based Systems Epistemology and Knowledge-Based Systems The Definition of Knowledge The Computer Configuration Problem The Dimensions of Knowledge Stages of Knowledge Knowledge in a Knowledge-Based System Knowledge Acquisition Knowledge Engineer-Guided Knowledge Acquisition Planning the Knowledge Acquisition Process Automated Tools for Knowledge Acquisition Induction Steps after Knowledge Acquisition Summary Bibliography and Suggested Readings Notes Chapter 3 — Representing and Reasoning with Knowledge Knowledge Representation Using Rules Complex Rules and Structured Rule-Based Systems Inference Procedures in Rule-Based Systems Forward Chaining Backward Chaining A Comparison of Backward and Forward Chaining Meta-Knowledge in Rule-Based Reasoning Rule-Based Reasoning Under Uncertainty Prolog: A Simple Rule-Based System The Inference Procedure of Prolog Benefits And Limitations of Rule-Based Reasoning Networked Representations of Knowledge Semantic Networks Frame Hierarchies Structure of Objects Behaviors of Objects Communication Between Objects Comparing Frame Hierarchies and Rules Alternative Approaches to Knowledge Representation Blackboard Systems Case-Based Reasoning Summary Bibliography and Suggested Readings Notes Part III — Implementing Strategic Knowledge Processing Applications Chapter 4 — Creating Knowledge-Based Systems Creating Rule-Based Systems Problem Description Problem Decomposition Initial Prototype Incremental Evolution Customization Structured Rule-Based Systems Creating Hybrid Knowledge-Based Systems Problem Description Frame Hierarchy Identification Structure and Behavior Identification Prototyping and Incremental Evolution Customization Customizing the User Interface Interfaces to Databases Tools for Building Knowledge-Based Systems Types of Shell Tools Hardware Platforms for Shell Tools Guidelines For The Selection of Shell Tools Commercial Market for Knowledge-Based Products The Database and Knowledge-Based Product Markets Summary Bibliography and Suggested Readings Notes Chapter 5 — Strategic And Organizational Issues in Knowledge Processing Levels of Organizational Knowledge Managing Knowledge in Organizations Knowledge-Based Systems and the Management of Knowledge Applications of Knowledge-Based Systems in Organizations The Task Perspective User Support Types The Systems Perspective Activity Types Organizational Benefits Organizational Hazards Impact on Industry Structures Managing the Development Process in Organizations Choosing a Corporate Strategy for Knowledge Processing Factors Affecting the Knowledge Processing Strategy Identification of Potential Knowledge-Based Applications Cost-Benefit Analyses of Potential Applications Determining Feasibility of Applications Creation of Knowledge-Based Applications Deployment of Applications Maintenance of Applications Summary Bibliography and Suggested Readings Notes Part IV — Intelligent Interfaces Chapter 6 — Natural Language Processing The Securities and Exchange Commission Siemens-Nixdorf Components of Natural Language Processing The Nature of Understanding Ambiguity in Natural Language Understanding Approaches to Natural Language Understanding Keyword Matching Syntax and Semantics Semantic Analyses Combining Syntax and Semantics Knowledge-Based Conceptual Dependency Diagrams Scripts Understanding Multiple Sentences and Dialogs Machine Translation Approaches to Machine Translation Pattern-Based Translation Using Syntax and Semantics for Translation Knowledge-Based Translation Machine Translation in Industry Evaluating Natural Language Interfaces Commercial Tools for Natural Language Processing Applications of Natural Language Processing The Securities and Exchange Commission The Intelligent Banking System at Citibank The Direct Labor Management System at Ford Content-Based Indexing of News Stories at Reuters Patient Medical Records System at Hartford Hospital Natural Language Applications at Steelcase The Business Impact of Natural Language Processing Summary Bibliography and Suggested Readings Notes Chapter 7 — Image and Speech Processing Computer Vision Biological Roots Computational Requirements Problems And Ambiguities Information Processing in Machine Vision Signal Processing Digitizing And Sampling Thresholding Smoothing Edge Detection Image Processing Segmentation Labeling Image Understanding Identification Interpretation Commercial Applications of Machine Vision Industrial Vision Applications Document Image Processing Retirement Fund Processing Yellow Pages Advertising Management Diagnosing Heart Imagery Microfossil Identification Speech Processing Interpretation Problems Speech Recognition Speech Understanding Speech Processing Phonetic Analysis Phonological Analysis Morphological Analysis The Business Impact of Image and Speech Processing Summary Bibliography and Suggested Readings Notes Part V — Alternative Approaches to Knowledge Processing Chapter 8 — Approximate Reasoning Using Fuzzy Logic Hitachi: The Sendai Subway Control System Yamaichi Securities: Intelligent Trading Programs Matshushita: Intelligent Washing Machines Rockwell: Modeling Stress on Wings Development of Fuzzy Logic Fundamentals of Fuzzy Logic Technology Representational Concepts Representation of Vague Concepts Using Fuzzy Sets Linguistic Variables Practical Implications of Fuzzy Set Representations Reasoning Procedures Mathematical Operations on Fuzzy Sets Inference With Frizzy Rules Comparing Fuzzy and Conventional Rules Case Studies of Fuzzy Logic Applications The Inverted Pendulum Fuzzy Rules for Balancing an Inverted Pendulum Properties of Fuzzy Control Complex Inverted Pendulum Systems Sendai Subway Control Commercial Activities in Fuzzy Logic Asia America Europe The Business Impacts of Fuzzy Logic Applications Enhancing Knowledge-Based Technologies Embedded Intelligence Intelligent Process Control New Product Development Strategies Summary Bibliography and Suggested Readings Notes Chapter 9 — Connectionist Modeling of Intelligence The Connectionist Approach History of Connectionism Governmental Support Neural Networks Problem Types Tackled by Neural Networks Classification Generalization Clustering Types of Neural Networks Selected Neural Network Architectures Multi-Layer Perceptrons Structure of Neurons Training Testing Learning Decision Regions Solved by Perceptrons The Hopfield Net Kohonen's Self-Organizing Feature Maps Designing Applications Using Neural Networks Domain and Problem Characteristics Designing the Network Training and Testing the Network Maintaining and Integrating Applications Commercial Tools Case Study: Using Neural Networks Ffor Bond Rating The Problem of Bond Rating Use Of Statistical Models for Bond Rating Decision Region Required for Bond Rating Selection of Variables Data Collection Neural Network Regression Results Applications of Neural Networks Nettalk Determining the Secondary Structure of Proteins Car Navigation Backgammon Diagnosis And Treatment Prescription for Hypertension Strengths And Limitations of Connectionist Models Limitations The Future of Symbolic and Connectionist Approaches Summary Bibliography and Suggested Readings Notes Appendix 1 — Commercial Applications of Knowledge-Based Systems Appendix 2 — Commercial Vendors of Knowledge-Based Products Appendix 3 — Commercial Applications of Neural NetworksIndex