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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Data Mining for Scientific and Engineering Applications

Data Mining for Scientific and Engineering Applications

Grossman, R. L.
Kamath, C.
Kegelmeyer, P.

Hardcover

Series: Massive Computing, Book 2

Medical ReferenceDatabasesGeneral Computers

ISBN10: 1402000332
ISBN13: 9781402000331
Publisher: Springer Nature
Published: Oct 31 2001
Pages: 605
Weight: 2.45
Height: 1.55 Width: 7.20 Depth: 9.18
Language: English
Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications.
Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

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