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Privacy-Preserving Data Mining: Models and Algorithms: 34 (Advances in Database Systems) - Tapa blanda
Sinopsis
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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De la contraportada
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.
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- EditorialSpringer
- Año de publicación2010
- ISBN 10 1441943714
- ISBN 13 9781441943712
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas536
- EditorAggarwal Charu C., Yu Philip S.
- Contacto del fabricanteno disponible
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EUR 65,22 gastos de envío desde Estados Unidos de America a España
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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: Models and Algorithms (Advances in Database Systems, 34)
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Occupies an important niche in the privacy-preserving data mining fieldSurvey information included with each chapter is unique in terms of its focus on introducing the different topics more comprehensivelyProvides relative und. Nº de ref. del artículo: 4174721
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Privacy-Preserving Data Mining
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Springer US, Springer US Nov 2010, 2010
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ISBN 13: 9781441943712
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9781441943712
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Privacy-Preserving Data Mining : Models and Algorithms
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ISBN 10: 1441943714
ISBN 13: 9781441943712
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9781441943712
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Privacy-Preserving Data Mining: Models and Algorithms (Advances in Database Systems, 34)
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Privacy-Preserving Data Mining
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ISBN 10: 1441943714
ISBN 13: 9781441943712
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Taschenbuch. Condición: Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 536 pp. Englisch. Nº de ref. del artículo: 9781441943712
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