- Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems
- Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support
- The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining
- More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining
- Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis
Data Mining Techniques
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Editorial Reviews
Review
"The book thoroughly acquaints you with the new generation of data mining tools and techniques and shows you how to use them to make better business decisions. This guide describes techniques for detecting customer behavior patterns useful in formulating marketing, sales and customer support strategies. While database analysts will find more than enough technical information to satisfy their curiosity, technically savvy business and marketing managers will find this book accessible." (Fathbrain.com; Ganthead.com, 9/01)
--This text refers to an out of print or unavailable edition of this title.
From the Publisher
With data mining, companies can analyze customers' past behaviors in order to make strategic decisions for the future. This book is a practical guide to mining business data to help marketers and business managers focus their marketing and sales strategies. It explains how each mining technique works and what kinds of business problems each one can solve.
--This text refers to an out of print or unavailable edition of this title.
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Most Helpful Customer Reviews
28 of 29 people found the following review helpful
Format:Paperback
It covers almost every aspect of data mining. It is clear, precise, goes to the point, and sometimes goes into some depth. If you are a marketing person, it will give you a very refined idea of what can be done with data mining, and what does it involves for your company ( remember the first thing you need is DATA!!). If you are an academic person, you will get a general idea of the different kinds of data analysis. You won't see any formulae or algorithms, after reading this book look for details somewhere else.
27 of 28 people found the following review helpful
Format:Paperback
Although this book was not written as a text book, we have noticed that it is frequently used that way. For the benefit of instructors, we have collected some exercises and datasets that can be used in the classroom or for self study. These can be found at www.data-miners.com/companion.
24 of 26 people found the following review helpful
Format:Paperback
This book gives an overview of what data mining is and the tools available to perform it; Market Basket Analysis, Memory Based Reasoning, Automatic Cluster Detection, Link Analysis, Decision Trees, Artificial Neural Networks. Genetic Algorithms are also included, which, while not a data mining tool, are being used to train neural nets.
In each case the authors describe the principles behind the tool, its strengths and weaknesses and applications were it is applicable. The authors give tips on what data preparation is required for the tool, both in terms of data "massaging", (which is required for neural nets) and indicate were it is important to select training sets that have approximately equal proportions of "good" & "bad" outcomes, in order for the tool to predict correctly.
The descriptions include simple examples of the tool to give an overview of how the tool works. But as the title indicates, this book is for users who are considering using data mining tools. It does not describe how to use particular applications, neither does it include code examples (pseudo or actual) if you are interesting in developing your own tools.
The book is easy to read and includes many examples from their experience of data mining in the real world.
Most Recent Customer Reviews
Great Information!
This is a very complete (large) book on data mining. Any questions that you may have, this book will answer them!
Published 12 months ago by Tracey Triedit
Good buck for the $$$
Sure its old but data mining techniques really haven't changed in the last 15 years. A great overview of the subject with real world applications.
Published 12 months ago by JimIvie
OK Book
This book - has a lot of content - all with quite good relevant examples.
Where this book fails is - in its technical details. Read more
Where this book fails is - in its technical details. Read more
Published 12 months ago by Sumit Pal
Data Mining Techniques
Excellent coverage of various aspects of data mining. Popular as a textbook (reason for purchase). Plenty of graphics and illustrations; written in clear and easily understood... Read more
Published on April 2, 2010 by W. Baggette
Data Mining book you should read first
Be careful, the first edition is MUCH older. Make sure you get the current 2004 edition.
There are most recent books, but this one is still worth reading first. Read more
There are most recent books, but this one is still worth reading first. Read more
Published on December 28, 2008 by Keith McCormick
Excellent book for Data Mining
As a novice to data mining, I was searching for a book that would explain the concepts, NOT mathematical formulas. Read more
Published on June 1, 2007 by Carl A. Boger
Very Interesting book
I'm very interesting in Data Mining and i think that this book is a good introduction to this field. Thanks Amazon
Published on May 12, 2007 by David R. Valles
A must-have book for your technical library
Anyone interested in automating and improving decisions should have this book. It is one of the classic works on data mining and well worth the read. Read more
Published on December 27, 2006 by James Taylor
Excellent introduction
This well-written book is an excellent introduction to the data mining and predictive analytics space. The reader should be comfortable with data and data analysis. Read more
Published on September 7, 2005 by T. Sawhney
Practical examples not convincing, lack of benchmarking
While the book is easy to read and not too technical, the applications investigated by the authors are too simplistic and not really convincing as to why we should use advanced... Read more
Published on June 16, 2005 by Vincent Granville
Inside This Book
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First Sentence:
Somerville, Massachusetts, home to one of the authors of this book, is also home to a woman from Cameroon who braids hair. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
moviegoers database, undirected data mining, applying market basket analysis, field distance functions, minimum support pruning, undirected knowledge discovery, record distance function, preclassified data, automatic cluster detection, adjusted error rate, data mining environment, most data mining techniques, virtual items, call detail data, other data mining techniques, candidate subtrees, central fact table, integrating data mining, generalized items, corporate data warehouse, neural network packages, data mining problems, data mining purposes, evaluation dataset, data mining effort Key Phrases - Capitalized Phrases (CAPs): (learn more)
United States, Bank of America, Technology Solutions, Capital One, First Union, Future View, The Wine Cask, Twenty Questions, Yellow Pages New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Somerville, Massachusetts, home to one of the authors of this book, is also home to a woman from Cameroon who braids hair. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
moviegoers database, undirected data mining, applying market basket analysis, field distance functions, minimum support pruning, undirected knowledge discovery, record distance function, preclassified data, automatic cluster detection, adjusted error rate, data mining environment, most data mining techniques, virtual items, call detail data, other data mining techniques, candidate subtrees, central fact table, integrating data mining, generalized items, corporate data warehouse, neural network packages, data mining problems, data mining purposes, evaluation dataset, data mining effort Key Phrases - Capitalized Phrases (CAPs): (learn more)
United States, Bank of America, Technology Solutions, Capital One, First Union, Future View, The Wine Cask, Twenty Questions, Yellow Pages New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 12
books:
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20
books
cite this book:
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- The Loyalty Effect: The Hidden Force Behind Growth, Profits, and Lasting Value by Frederick F. Reichheld on page 2, and Back Matter
- Cluster Analysis for Applications (Probability & Mathematical Statistics Monograph) by Michael R. Anderberg on page 200, and Back Matter
- Judgment Day by James F. David on page 58, and page 390
- Enterprise One to One by Don Peppers on page 111, and Back Matter
- Building the Data Warehouse by W. H. Inmon in Back Matter
See all 12 books this book cites
- Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents: Second International ... (Lecture Notes in Computer Science) by Kwong S. Leung on page 34, and page 179
- Data Mining and Decision Support: Integration and Collaboration (The Springer International Series in Engineering and Computer Science) by Dunja Mladenic on page 77, and page 130
- The Next Wave in Computing, Optimization, and Decision Technologies (Operations Research/Computer Science Interfaces Series) by Bruce L. Golden on page 353
- Geospatial Data Infrastructure : Concepts, Cases, and Good Practice (Spatial Information Systems (Cloth)) by Richard Groot on page 230
- Visual Data Mining: Techniques and Tools for Data Visualization and Mining by Tom Soukup in Back Matter
See all 20 books citing this book
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