743 search results - page 40 / 149 » Performance Measurements for Privacy Preserving Data Mining |
133
Voted
SDM
2007
SIAM
15 years 3 months ago
2007
SIAM
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
110
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ISI
2008
Springer
15 years 1 months ago
2008
Springer
Often several cooperating parties would like to have a global view of their joint data for various data mining objectives, but cannot reveal the contents of individual records due...
98
Voted
PVLDB
2010
15 years 8 days ago
2010
Random perturbation is a promising technique for privacy preserving data mining. It retains an original sensitive value with a certain probability and replaces it with a random va...
222
Voted
ICDE
2007
IEEE
16 years 3 months ago
2007
IEEE
A key method for privacy preserving data mining is that of randomization. Unlike k-anonymity, this technique does not include public information in the underlying assumptions. In ...
KDD
2006
ACM
16 years 2 months ago
2006
ACM
Protecting data privacy is an important problem in microdata distribution. Anonymization algorithms typically aim to protect individual privacy, with minimal impact on the quality...