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Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)
 
 

Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems) (Hardcover)

by Jiawei Han (Author), Micheline Kamber (Author) "This book is an introduction to what come to known as data mining and knowledge spective, where emphasis is placed on basic data mining concepts..." (more)
4.3 out of 5 stars  See all reviews (3 customer reviews)
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Price For All Three: £116.60

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Product details

  • Hardcover: 550 pages
  • Publisher: Morgan Kaufmann (6 Sep 2000)
  • Language English
  • ISBN-10: 1558604898
  • ISBN-13: 978-1558604896
  • Product Dimensions: 23.8 x 19 x 3 cm
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon.co.uk Sales Rank: 492,610 in Books (See Bestsellers in Books)

    Popular in this category:

    #31 in  Books > Computing & Internet > Databases > Data Storage & Management > Data Mining
  • See Complete Table of Contents

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Product Description

Review

"many excellent features" -- Tony Jenkins,Vice Chairman, British Computer Society's, Data Management Specialist Group


Product Description

Here's the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges. Data Mining: Concepts and Techniques equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery in large corporate databases.

Written expressly for database practitioners and professionals, this book begins with a conceptual introduction designed to get you up to speed. This is followed by a comprehensive and state-of-the-art coverage of data mining concepts and techniques. Each chapter functions as a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. Wherever possible, the authors raise and answer questions of utility, feasibility, optimization, and scalability, keeping your eye on the issues that will affect your project's results and your overall success.

Data Mining: Concepts and Techniques is the master reference that practitioners and researchers have long been seeking. It is also the obvious choice for academic and professional classrooms.

Classroom Features Available Online:
- instructor's manual
- course slides (in PowerPoint)
- course supplementary readings
- sample assignments and course projects

* Offers a comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data.
* Organized as a series of stand-alone chapters so you can begin anywhere and immediately apply what you learn.
* Presents dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects.
* Provides in-depth, practical coverage of essential data mining topics, including OLAP and data warehousing, data preprocessing, concept description, association rules, classification and prediction, and cluster analysis.
* Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields.

Inside This Book (Learn More)
First Sentence
This book is an introduction to what come to known as data mining and knowledge spective, where emphasis is placed on basic data mining concepts and techniques for uncovering interesting data patterns hidden in large data sets. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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3 Reviews
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Average Customer Review
4.3 out of 5 stars (3 customer reviews)
 
 
 
 
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Most Helpful Customer Reviews

 
4 of 4 people found the following review helpful:
5.0 out of 5 stars An excellent data mining book, 13 Mar 2004
By A Customer
If you are interesting to understand the principles of data mining in large corporate databases, then this book should be your first choice. It presents dozens of algorithms and implementation examples -in pseudocode- .

The book takes the reader through the whole processes of knowledge discovery in large database, explaining each process in great details and answering why it needs to be done. The book has a good coverage of data preparation/preprocessing, association rules, classification and prediction, and cluster analysis.

If you are looking for a book that covers advance topics in data mining such as time-series databases, text-databases, spatial databases, then, you need to look for another book that covers them in more details. However, this book needs to be in your bookshelf as the basis for understanding data mining in large database.

In general, the book is easy to read with many diagrams illustrating the concepts. Also, it provides the reader with the current trend research areas in data mining.

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4 of 4 people found the following review helpful:
5.0 out of 5 stars Very Good, 18 Feb 2004
By Chris (Europe) - See all my reviews
This is a very good book, with thourough explanations
Altough I initialy used as a classbook, I still found it useful for researching and application develoment.
It doesn't assume any knowledge in this field but still is not boring for people already aware of data mining principles.
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3.0 out of 5 stars Overview, 28 Oct 2009
By Eng Nuno R. Ferreira (Portugal) - See all my reviews
(REAL NAME)   
I thought the book was a bit more detailed, with some examples, althougth, it explains well dataminig terms.
It's indicated for someone that it's starting in the area
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