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Privacy-Preserving Data Mining: Models and Algorithms: 34 (Advances in Database Systems, 34) - Softcover
Synopsis
This book proposes a number of techniques to perform data mining tasks in a privacy-preserving way. The survey information included with each chapter is unique in terms of its focus on introducing the different topics more comprehensively.
"synopsis" may belong to another edition of this title.
Review
From the reviews:
"This book provides an exceptional summary of the state-of-the-art accomplishments in the area of privacy-preserving data mining, discussing the most important algorithms, models, and applications in each direction. The target audience includes researchers, graduate students, and practitioners who are interested in this area. ... I recommend this book to all readers interested in privacy-preserving data mining." (Aris Gkoulalas-Divanis, ACM Computing Reviews, October, 2008)
From the Back Cover
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.
Privacy Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques. This edited volume also contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy.
Privacy Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science. This book is also suitable for practitioners in industry.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2010
- ISBN 10 1441943714
- ISBN 13 9781441943712
- BindingPaperback
- LanguageEnglish
- Number of pages536
- EditorAggarwal Charu C., Yu Philip S.
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Privacy-Preserving Data Mining: Models and Algorithms (Advances in Database Systems)
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Springer November 2010, 2010
ISBN 10: 1441943714
ISBN 13: 9781441943712
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Privacy-Preserving Data Mining
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ISBN 10: 1441943714
ISBN 13: 9781441943712
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes.Privacy-Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques.This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions.Privacy-Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science, and is also suitable for industry practitioners. 536 pp. Englisch. Seller Inventory # 9781441943712
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Privacy-Preserving Data Mining : Models and Algorithms
Published by
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ISBN 10: 1441943714
ISBN 13: 9781441943712
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes.Privacy-Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques.This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions.Privacy-Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science, and is also suitable for industry practitioners. Seller Inventory # 9781441943712
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Privacy-Preserving Data Mining: Models and Algorithms (Advances in Database Systems)
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