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Books by Data Miners Staff

Praise for Mastering Data Mining :

"This is a great book, and it will be in my stack of four or five essential resources for my professional work."-
Ralph Kimball, author of The Data Warehouse Lifecycle Toolkit

Praise for Data Mining Techniques:

"Clear and lucid writing coupled with useful, real-world examples... Highly recommended."
-Robert Craig, Director, Data Warehousing and Business Intelligence, Hurwitz Group

Praise for Data Preparation for Data Mining :

"A good book for understanding the structure and content of data required for data mining."
- Ralph Kimball & Richard Merz, The Data Webhouse Toolkit

Mining the Web
by Michael J.A. Berry and Gordon S. Linoff
copyright 2002 by John Wiley & Sons
ISBN 0-471-41609-6

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This book looks at the new opportunities and challenges for data mining that have been created by the web. The book demonstrates how to apply data mining to specific types of online businesses, such as auction sites, B2B trading exchanges, click-and-mortar retailers, subscription sites, and online retailers of digital content.

Mastering Data Mining
by Michael J.A. Berry and Gordon S. Linoff
copyright 2000 by John Wiley & Sons
ISBN 0-471-33123-6

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A case study-based guide to applying data mining techniques for solving practical business problems. These "warts and all" case studies are drawn directly from consulting engagements performed by the authors.
Also available in Japanese, Chinese and Italian !

Data Mining Techniques
by Michael J. A. Berry and Gordon S. Linoff
copyright 1997 by John Wiley & Sons
ISBN 0-471-47064-3

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The second edition of this favorite introduction to data mining has been extensively revised, expaned, and updated. Covers all major data mining techniques including neural networks, decision trees, clustering, association rules, genetic algorithms, memory-based reasoning and other nearest-neighbor techniques, and survival analysis. The techniques are described in clear, simple language and are illustrated with examples taken from actual data mining engagements performed by the authors.
The first edition is available en francais and in Japanese and Chinese!

Data Preparation for Data Mining
by Dorian Pyle
copyright 1999 by Morgan Kaufmann
ISBN 1-55860-529-0

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This book addresses a crucial issue often ignored in data mining: data preparation. Including a conceptual overview for managers as well as full technical details for miners and modelers, the book shares Dorian's own data preparation methodology. Apply his techniques and watch your mining performance improve and yield more valuable results. The only book entirely devoted to this topic! Includes CD-ROM.

Business Modeling and Data Mining
by Dorian Pyle
Morgan Kaufmann Publishers, Inc.
ISBN 1-55860-653-X

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Dorian's next book answers two key questions for data miners: 1) How do you turn business descriptions of problems into a form that can be answered by data mining? and 2) What business problems can data mining usefully address, and how? It also presents a clear, broadly applicable methodology for building well-defined quantitative models, as well as tips on how to garner support for data mining projects.

Handbook of Data Mining
Dorian Pyle, Contributor
Copyright 2003 Lawrence Erlbaum Associates

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Dorian was invited to contribute a chapter on "Data Collection, Preparation, Quality, and Visualization". This chapter provides an overview of the issues of data collection, data preparation, data quality, and data visualization, and recounts the main principles required in order to effectively prepare data for mining.

Web Usage Analysis and User Profiling
Myra Spiliopoulou and Brij Masand (ed's)
copyright 2000 by Springer-Verlag
ISBN 3-540-67818-2

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This book originates from the WEBKDD'99 Workshop held during the 1999 KDD Conference. The 10 revised full papers presented together with an introductory survey by the volume editors documents the state of the art in this area. The book presents topical sections on Modeling the User, Discovering Rules and Patterns of Navigation, and Measuring interestingness in Web Usage Mining.