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Reviewer:

Computer technology has been motivated by a number of other disciplines, including biology, neurology, psychology, statistics, and computer science. The field of AI has provided an instrument for integrating the ideas from these disciplines by comparing them in terms of their power to solve various types of problems. This book is for business professionals who are interested in knowing how these technologies can be used profitably in business. The authors use modeling techniques that have emerged over the past few decades, including the symbolic, connectionist, evolutionary, and inductive approaches. Time database technology and online analytical processing are used to access organizational data. Collectively, the tools described in this textbook allow organizations to access, view, understand, and manipulate data more easily in order to make decisions. This book is organized into ten interesting chapters. The first chapter is an introduction and presents a taxonomy of management information systems. Chapter 2 discusses intelligence density as a measure of organizational intelligence. Chapter 3 is devoted to the vocabulary of intelligence density. It covers such topics as the dimensions of problems and solutions; a vocabulary for requirements and analysis, called the Stretch Plot; and the use of the Stretch Plot. Chapters 4 through 10 discuss seven different methods for transforming corporate data into business intelligence: data-driven decision support, evolving solutions, neural networks, rule-based systems, fuzzy logic, case-based reasoning, and machine learning. References and additional reading lists are provided at the end of each chapter of the book.