Data Mining and Knowledge Discovery Handbook [Hardcover]

Oded Maimon (Editor), Lior Rokach (Editor)

RRP:	�197.00
Price:	�187.15 & this item Delivered FREE in the UK with Super Saver Delivery. See details and conditions
Deal Price:
You Save:	�9.85 (5%)
	o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o

In stock but may require up to 2 additional days to deliver.
Dispatched from and sold by Amazon.co.uk. Gift-wrap available.

Only 1 left in stock--order soon (more on the way).

Amazon.co.uk Trade-In Store
Did you know you can trade in your old books for an Amazon.co.uk Gift Card to spend on the things you want? Visit the Amazon.co.uk Trade-In Store for more details.

› See more product promotions

There is a newer edition of this item:

Data Mining and Knowledge Discovery Handbook
�171.00

Usually dispatched within 1 to 3 weeks

Product details

Hardcover: 1383 pages
Publisher: Springer (25 Oct 2005)
Language English
ISBN-10: 0387244352
ISBN-13: 978-0387244358
Product Dimensions: 24.1 x 16.3 x 6.6 cm
Amazon Bestsellers Rank: 3,680,361 in Books (See Top 100 in Books)

Would you like to update product info or give feedback on images?

See Complete Table of Contents

More About the Author

Discover books, learn about writers, and more.

› Visit Amazon's Lior Rokach Page

Product Description

Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.

Inside This Book (Learn More)

Explore More
Concordance

Tag this product

(What's this?)

Think of a tag as a keyword or label you consider is strongly related to this product.
Tags will help all customers organise and find favourite items.

Sell a Digital Version of This Book in the Kindle Store

If you are a publisher or author and hold the digital rights to a book, you can sell a digital version of it in our Kindle Store. Learn more

Customer Reviews

There are no customer reviews yet on Amazon U.K.

5 star:		(0)
4 star:		(0)
3 star:		(0)
2 star:		(0)
1 star:		(0)

Share your experience with this product with others

Create your own review

Most Helpful Customer Reviews on Amazon.com ^(beta)

Amazon.com: 4.0 out of 5 stars (2 customer reviews)

7 of 8 people found the following review helpful:

5.0 out of 5 stars A great handbook for data mining, 12 April 2006

By James Franklin - Published on Amazon.com

This review is from: Data Mining and Knowledge Discovery Handbook (Hardcover)

I'm surprisingly pleased with this book. The book is well-written and it is completely worth the price. The main chapters of the book are independent, so you can read them in any order. It nearly cover the entire data mining field. In fact you can find a good overview about almost all important data mining techniques. Moreover most of the algorithms are presented in pseudo code, so you can really learn how to implement them. I also liked the application section which describes real case studies - it gives you a good sense how to use these techinques.

3 of 3 people found the following review helpful:

3.0 out of 5 stars The Curate's Egg, 15 Jun 2008

By Chris Hobbs "cwlh" - Published on Amazon.com

This review is from: Data Mining and Knowledge Discovery Handbook (Hardcover)

This is a book (calling it a "handbook" implies that data miners have particularly large hands) of papers, loosely divided into subject areas.

The first thing to be said is that the index is rubbish. For such a large book it is totally inadequate (5 pages for a 1383 page book!), the level of indexing fluctuates wildly and there are some really strange errors:

Decision Tree 1114
Decision support systems ......
Decision table majority 99, 105
Decision tree 150, 165, 167, 314

That "Decision Tree" should be sorted away from "Decision tree" is understandable to anyone who knows ASCII but surely even then the two entries shouldn't be split by "Decision support". I also liked:

GLM (Generalized Linear Model) 240, 575
GLM (Generalized Linear Models) 213, 215

In general, the quality of the index reflects the general quality of the editing: poor. I have been involved in contributing a chapter to a book of this sort and know that it is very difficult for the editor to maintain a constant vocabulary, level and thrust throughout a book of contributed papers but this one is worse than normal: some authors simply repeat what previous authors have said, some contradict.

So, is this worth the best part of $200? If you are looking for a review of data mining techniques without a great deal of mathematical maturity being required then this is probably a reasonable book. Many of the papers cover the ground of a particular technique very well. What is lacking is the map of the wood as well as the details of each tree. There is one overview paper at the front but it introduces terminology that is not generally followed later.

The final section, examples of the use of data mining in various industrial situations (finance, telecommunications, etc.), is very superficial and does not tie into the other papers at all. It would have been worthwhile for the editor to have collected the earlier papers (tools and techniques) and provided these to the writers of the industrial examples. It would have been really useful to have tied the examples to the particular techniques: "Using the XYZ technique as described in Fred's paper on page 123 of this handbook, ....".

In summary, I don't regret having bought this book and I have learned from it but, with strong editing, it could have been 1000 times better.

› Go to Amazon U.S. to see both reviews 4.0 out of 5 stars

Were these reviews helpful? Let us know

.jsOffDisplayBlock { display: block; } .jsOffDisplayInline { display: inline; } .jsOffVisibility { visibility: visible; } .jsOnDisplayBlock { display: none; } .jsOnDisplayNoneBlock { display: block; } .jsOnDisplayNoneInline { display: inline; } .jsOnDisplayInline { display: none; } .jsOnVisibility { visibility: hidden; } .jqOnDisplayBlock { display: none; } .jqOnDisplayInline { display: none; } .jqOnVisibility { visibility: hidden; } .jqOnDisplayNoneBlock { display: block; } .jqOnDisplayNoneInline { display: inline; }