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Data Mining for Scientific and Engineering Applications
. Ed(S): Grossman, Robert L.; Kamath, Chandrika; Kegelmeyer, P.; Kumar, V.
€ 268.11
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Description for Data Mining for Scientific and Engineering Applications
Paperback. Illustrates the diversity of problems and application areas that can benefit from data mining, as well as issues and challenges that differentiate scientific data mining from its commercial counterpart. This book focuses on mining scientific data. It is suitable for students and researchers who are familiar with basic principles of data mining. Editor(s): Grossman, Robert L.; Kamath, Chandrika; Kegelmeyer, P.; Kumar, V. Series: Massive Computing. Num Pages: 605 pages, biography. BIC Classification: UN. Category: (G) General (US: Trade); (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 240 x 160 x 32. Weight in Grams: 1910.
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 ... Read more
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 ... Read more
Product Details
Format
Paperback
Publication date
2001
Publisher
Kluwer Academic Publishers United States
Number of pages
605
Condition
New
Series
Massive Computing
Number of Pages
605
Place of Publication
New York, NY, United States
ISBN
9781402001147
SKU
V9781402001147
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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