Next Generation of Data-Mining Applications

Cover Image Copyright Year: 2005
Author(s): Mehmed Kantardzic; Jozef Zurada
Book Type: Wiley-IEEE Press
Content Type : Books
Topics: Communication, Networking & Broadcasting ;  Computing & Processing
  • Print


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
  • Bioinform tics 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 undergr duate and graduate courses in computer science, information management, and statistics.