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» Privacy-preserving data mashup
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DAWAK
2006
Springer
15 years 1 months ago
Two New Techniques for Hiding Sensitive Itemsets and Their Empirical Evaluation
Many privacy preserving data mining algorithms attempt to selectively hide what database owners consider as sensitive. Specifically, in the association-rules domain, many of these ...
Ahmed HajYasien, Vladimir Estivill-Castro
PVLDB
2010
95views more  PVLDB 2010»
14 years 8 months ago
Small Domain Randomization: Same Privacy, More Utility
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...
Rhonda Chaytor, Ke Wang
WWW
2009
ACM
15 years 4 months ago
Rapid prototyping of semantic mash-ups through semantic web pipes
The use of RDF data published on the Web for applications is still a cumbersome and resource-intensive task due to the limited software support and the lack of standard programmin...
Danh Le Phuoc, Axel Polleres, Manfred Hauswirth, G...
AUSDM
2006
Springer
157views Data Mining» more  AUSDM 2006»
15 years 1 months ago
Safely Delegating Data Mining Tasks
Data mining is playing an important role in decision making for business activities and governmental administration. Since many organizations or their divisions do not possess the...
Ling Qiu, Kok-Leong Ong, Siu Man Lui
ICDE
2012
IEEE
221views Database» more  ICDE 2012»
13 years 6 days ago
DPCube: Releasing Differentially Private Data Cubes for Health Information
—We demonstrate DPCube, a component in our Health Information DE-identification (HIDE) framework, for releasing differentially private data cubes (or multi-dimensional histogram...
Yonghui Xiao, James J. Gardner, Li Xiong