Privacy Preserving Data Mining
- Indbinding:
- Paperback
- Sideantal:
- 132
- Udgivet:
- 19. november 2010
- Størrelse:
- 155x8x235 mm.
- Vægt:
- 213 g.
- 8-11 hverdage.
- 7. december 2024
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- Adgang til 70.000+ titler
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Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Privacy Preserving Data Mining
Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are growing that use of this technology can violate individual privacy. These concerns have led to a backlash against the technology, for example, a "Data-Mining Moratorium Act" introduced in the U.S. Senate that would have banned all data-mining programs (including research and development) by the U.S. Department of Defense.
Privacy Preserving Data Mining provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. This book demonstrates how these approaches can achieve data mining, while operating within legal and commercial restrictions that forbid release of data. Furthermore, this research crystallizes much of the underlying foundation, and inspires further research in the area.
Privacy Preserving Data Mining is designed for a professional audience composed of practitioners and researchers in industry. This volume is also suitable for graduate-level students in computer science.
Privacy Preserving Data Mining provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. This book demonstrates how these approaches can achieve data mining, while operating within legal and commercial restrictions that forbid release of data. Furthermore, this research crystallizes much of the underlying foundation, and inspires further research in the area.
Privacy Preserving Data Mining is designed for a professional audience composed of practitioners and researchers in industry. This volume is also suitable for graduate-level students in computer science.
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Bogen Privacy Preserving Data Mining findes i følgende kategorier:
- Business og læring > Computer og IT
- Reference, information og tværfaglige emner > Forskning og information: generelt > Informationsteori
- Reference, information og tværfaglige emner > Forskning og information: generelt > Kodeteori og kryptologi
- Databehandling og informationsteknologi > Computere og hardware > Netværkskomponenter
- Databehandling og informationsteknologi > Programmering / softwareudvikling > Algoritmer og datastrukturer
- Databehandling og informationsteknologi > Databaser > Data warehouse
- Databehandling og informationsteknologi > Databaser > Data mining
- Databehandling og informationsteknologi > Databaser > Informationssøgning og informationsgenfinding
- Databehandling og informationsteknologi > Datasikkerhed > Datakryptering
- Databehandling og informationsteknologi > Informatik > Kunstig intelligens > Ekspertsystemer og vidensbaserede systemer
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