Data Mining: Concepts and Techniques
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Data Mining: Concepts and Techniques
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Preface
Our capabilities of both generating and collecting data have been increasing rapidly in the last several decades.
Contributing factors include the widespread use of bar codes for most commercial products, the computerization
of many business, scienti c and government transactions and managements, and advances in data collection tools
ranging from scanned texture and image platforms, to on-line instrumentation in manufacturing and shopping, and to
satellite remote sensing systems. In addition, popular use of the World Wide Web as a global information system has

ooded us with a tremendous amount of data and information. This explosive growth in stored data has generated
an urgent need for new techniques and automated tools that can intelligently assist us in transforming the vast
amounts of data into useful information and knowledge.

To the teacher
This book is designed to give a broad, yet in depth overview of the eld of data mining. You will nd it useful
for teaching a course on data mining at an advanced undergraduate level, or the rst-year graduate level. In
addition, individual chapters may be included as material for courses on selected topics in database systems or in
arti cial intelligence. We have tried to make the chapters as self-contained as possible. For a course taught at the
undergraduate level, you might use chapters 1 to 8 as the core course material. Remaining class material may be
selected from among the more advanced topics described in chapters 9 and 10. For a graduate level course, you may
choose to cover the entire book in one semester.


To the student
We hope that this textbook will spark your interest in the fresh, yet evolving eld of data mining. We have attempted
to present the material in a clear manner, with careful explanation of the topics covered. Each chapter ends with a
summary describing the main points. We have included many gures and illustrations throughout the text in order
to make the book more enjoyable and \reader-friendly". Although this book was designed as a textbook, we have
tried to organize it so that it will also be useful to you as a reference book or handbook, should you later decide to
pursue a career in data mining.

To the professional
This book was designed to cover a broad range of topics in the eld of data mining. As a result, it is a good handbook
on the subject. Because each chapter is designed to be as stand-alone as possible, you can focus on the topics that
most interest you. Much of the book is suited to applications programmers or information service managers like
yourself who wish to learn about the key ideas of data mining on their own.

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