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Privacy preserving data mining

Author: Jaideep Vaidya; Michael Zhu; Christopher Wade Clifton
Publisher: New York : Springer, ©2006.
Series: Advances in information security, v. 19.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
"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  Read more...
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Additional Physical Format: Online version:
Vaidya, Jaideep.
Privacy preserving data mining.
New York : Springer, ©2006
(OCoLC)209967495
Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Jaideep Vaidya; Michael Zhu; Christopher Wade Clifton
ISBN: 9780387258867 0387258868 0387294899 9780387294896
OCLC Number: 61424926
Description: 120 pages : illustrations ; 24 cm.
Contents: 1. Privacy and data mining --
2. What is privacy? --
3. Solution approaches/problems --
4. Predictive modeling for classification --
5. Predictive modeling for regression --
6. Finding patterns and rules (association rules) --
7. Descriptive modeling (clustering, outlier detection) --
8. Future research: problems remaining.
Series Title: Advances in information security, v. 19.
Responsibility: by Jaideep Vaidya, Chris Clifton, Michael Zhu.
More information:

Abstract:

Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data.  Read more...

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