Knowledge Processing and Applied Artificial Intelligence

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.

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

Notes

Part 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 Networks

Index