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» On Anonymization of String Data
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ICDE
2007
IEEE
115views Database» more  ICDE 2007»
15 years 10 months ago
MultiRelational k-Anonymity
k-Anonymity protects privacy by ensuring that data cannot be linked to a single individual. In a k-anonymous dataset, any identifying information occurs in at least k tuples. Much...
Mehmet Ercan Nergiz, Chris Clifton, A. Erhan Nergi...
CLUSTER
2008
IEEE
15 years 3 months ago
Enabling lock-free concurrent fine-grain access to massive distributed data: Application to supernovae detection
—We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and ac...
Bogdan Nicolae, Gabriel Antoniu, Luc Bougé
BMCBI
2010
86views more  BMCBI 2010»
14 years 9 months ago
Fast motif recognition via application of statistical thresholds
Background: Improving the accuracy and efficiency of motif recognition is an important computational challenge that has application to detecting transcription factor binding sites...
Christina Boucher, James King
AAAI
2007
14 years 11 months ago
A Randomized String Kernel and Its Application to RNA Interference
String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...
Shibin Qiu, Terran Lane, Ljubomir J. Buturovic
DBSEC
2009
112views Database» more  DBSEC 2009»
14 years 10 months ago
Distributed Anonymization: Achieving Privacy for Both Data Subjects and Data Providers
There is an increasing need for sharing data repositories containing personal information across multiple distributed and private databases. However, such data sharing is subject t...
Pawel Jurczyk, Li Xiong