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Privacy-Preserving Data Mining: Models and Algorithms

PUBLISHER Springer (11/19/2010)
PRODUCT TYPE Paperback (Paperback)

Description

Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals. This has caused concerns that personal data may be used for a variety of intrusive or malicious purposes. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. The survey information included with each chapter is unique in terms of its focus on introducing the different topics more comprehensively. Key advances in privacy that have appeared only in the past three years are covered. The book is designed for researchers, professors, and advanced-level students in computer science. It is also suitable for practitioners in industry.

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Product Format
Product Details
ISBN-13: 9781441943712
ISBN-10: 1441943714
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
More Product Details
Page Count: 514
Carton Quantity: 16
Product Dimensions: 6.14 x 1.08 x 9.21 inches
Weight: 1.64 pound(s)
Country of Origin: NL
Subject Information
BISAC Categories
Computers | Security - Network Security
Computers | Security - Cryptography & Encryption
Computers | Data Science - Data Analytics
Dewey Decimal: 005.74
Descriptions, Reviews, Etc.
publisher marketing

Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals. This has caused concerns that personal data may be used for a variety of intrusive or malicious purposes. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. The survey information included with each chapter is unique in terms of its focus on introducing the different topics more comprehensively. Key advances in privacy that have appeared only in the past three years are covered. The book is designed for researchers, professors, and advanced-level students in computer science. It is also suitable for practitioners in industry.

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Editor: Aggarwal, Charu C.
Charu C. Aggarwal obtained his B.Tech in Computer Science from IIT Kanpur in 1993 and Ph.D. from MIT in 1996. He has been a Research Staff Member at IBM since then, and has published over 90 papers in major conferences and journals in the database and data mining field. He has applied for or been granted over 50 US and International patents, and has twice been designated Master Inventor at IBM for the commercial value of his patents. He has been granted 14 invention achievement awards by IBM for his patents. His work on real time bio-terrorist threat detection in data streams won the IBM Epispire award for environmental excellence in 2003. He has served on the program committee of most major database conferences, and was program chair for the Data Mining and Knowledge Discovery Workshop, 2003, and a program vice-chair for the SIAM Conference on Data Mining, 2007. He is an associate editor of the IEEE Transactions on Data Engineering and an action editor of the Data Mining and Knowledge Discovery Journal. He is a senior member of the IEEE.
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List Price $239.00
Your Price  $236.61
Paperback