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Cook - Mining Graph Data - 9780471731900 - V9780471731900
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Mining Graph Data

€ 174.12
FREE Delivery in Ireland
Description for Mining Graph Data Hardcover. This books illustrates how data mining techniques, through the application of algorithms and graphs, have been responding to the need for the collection and storage of larger and more complex volumes of data. Editor(s): Cook, Diane J.; Holder, Lawrence B. Num Pages: 500 pages, Illustrations. BIC Classification: PBK. Category: (P) Professional & Vocational. Dimension: 235 x 163 x 33. Weight in Grams: 842.
This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal background in analyzing graph data, with this book you’ll be able to represent data as graphs, extract patterns and concepts from the data, and apply the methodologies presented in the text to real datasets.

There is a misprint with the link to the accompanying Web page for this book. For those readers who would like to experiment with the techniques found in this book or test their ... Read more

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Product Details

Format
Hardback
Publication date
2006
Publisher
John Wiley & Sons Inc United States
Number of pages
500
Condition
New
Number of Pages
512
Place of Publication
, United States
ISBN
9780471731900
SKU
V9780471731900
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50

About Cook
DIANE J. COOK, PhD, is the Huie-Rogers Chair Professor in the School of Electrical Engineering and Computer Science at Washington State University. Her extensive research in artificial intelligence and data mining has been supported by grants from the National Science Foundation, NASA, DARPA, and Texas Instruments. Dr. Cook is the coauthor of Smart Environments: Technology, Protocols, and Applications (Wiley). ... Read more

Reviews for Mining Graph Data
"…individuals with no background analyzing graph data can learn how to represent the data as graphs, extract patterns or concepts from the data, and see how researchers apply the methodologies to real datasets." (Computing Reviews.com, March 23, 2007)

Goodreads reviews for Mining Graph Data


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