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[H746.Ebook] Free Ebook Next Generation of Data-Mining ApplicationsFrom Wiley-IEEE Press

Free Ebook Next Generation of Data-Mining ApplicationsFrom Wiley-IEEE Press

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Next Generation of Data-Mining ApplicationsFrom Wiley-IEEE Press

Next Generation of Data-Mining ApplicationsFrom Wiley-IEEE Press



Next Generation of Data-Mining ApplicationsFrom Wiley-IEEE Press

Free Ebook Next Generation of Data-Mining ApplicationsFrom Wiley-IEEE Press

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Next Generation of Data-Mining ApplicationsFrom Wiley-IEEE Press

* This book presents the next generation of data mining applications based on state-of-the art methodologies and techniques for analyzing enormous quantities of raw data in high-dimension
* Each chapter describes the data mining development process, results, and experiences with new data mining tools and techniques
* Includes twenty-five novel and diverse contributions from experienced and well-respected data mining scientists and practitioners that describe their recent applications using state-of-the-art methods and algorithms

  • Sales Rank: #5411552 in Books
  • Published on: 2005-03-08
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.41" h x 1.46" w x 6.30" l, 2.42 pounds
  • Binding: Hardcover
  • 696 pages

Review
"…the book is a highly authoritative, cohesive and timely exposure to the recent developments, application areas and future trends in DM. This is must reading for a wide audience of practitioners and researchers." (Mathematical Reviews, 2006e)

"…a vast and comprehensive collection of chapters…" (Technometrics, November 2005)

"All the major applications of data mining...are covered in detail from the leaders in the field. I recommend this text to practitioners and researchers alike." (Computing Reviews.com, July 26, 2005)

From the Back Cover
Discover the next generation of data-mining tools and technology

This book brings together an international team of eighty experts to present readers with the next generation of data-mining applications. Unlike other publications that take a strictly academic and theoretical approach, this book features authors who have successfully developed data-mining solutions for a variety of customer types. Presenting their state-of-the-art methodologies and techniques, the authors show readers how they can analyze enormous quantities of data and make new discoveries by connecting key pieces of data that may be spread across several different databases and file servers. The latest data-mining techniques that will revolutionize research across a wide variety of fields including business, science, healthcare, and industry are all presented. Organized by application, the twenty-five chapters cover applications in:

  • Industry and business
  • Science and engineering
  • Bioinformatics and biotechnology
  • Medicine and pharmaceuticals
  • Web and text-mining
  • Security
  • New trends in data-mining technology
  • And much more . . .

Readers from a variety of disciplines will learn how the next generation of data-mining applications can radically enhance their ability to analyze data and open the doors to new opportunities. Readers will discover:

  • New data-mining tools to automate the evaluation and qualification of sales opportunities
  • The latest tools needed for gene mapping and proteomic data analysis
  • Sophisticated techniques that can be engaged in crime fighting and prevention

With its coverage of the most advanced applications, Next Generation of Data-Mining Applications is essential reading for all researchers working in data mining or who are tasked with making sense of an ever-growing quantity of data. The publication also serves as an excellent textbook for upper-level undergraduate and graduate courses in computer science, information management, and statistics.

About the Author
MEHMED M. KANTARDZIC, PhD, is Associate Professor and Director of the Data Mining Laboratory at the University of Louisville. He is the author of five books in data mining, including Data Mining: Concepts, Models, Methods, and Algorithms (Wiley-IEEE Press), and has published more than 120 articles in refereed journals and conference proceedings.

JOZEF ZURADA, PhD, is an associate professor at the University of Louisville. He is the coauthor of Knowledge Discovery for Business Information Systems and has published numerous articles in refereed journals and conference proceedings.

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Next Generation of Data-Mining ApplicationsFrom Wiley-IEEE Press PDF

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