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» Modeling and Integrating Background Knowledge in Data Anonym...
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SP
2008
IEEE
14 years 2 months ago
Robust De-anonymization of Large Sparse Datasets
We present a new class of statistical deanonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. ...
Arvind Narayanan, Vitaly Shmatikov
ICCV
2005
IEEE
14 years 9 months ago
Integration of Conditionally Dependent Object Features for Robust Figure/Background Segmentation
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and p...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
BMCBI
2004
161views more  BMCBI 2004»
13 years 7 months ago
Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatme
Background: To cancel experimental variations, microarray data must be normalized prior to analysis. Where an appropriate model for statistical data distribution is available, a p...
Tomokazu Konishi
CIKM
2010
Springer
13 years 5 months ago
Anonymizing data with quasi-sensitive attribute values
We study the problem of anonymizing data with quasi-sensitive attributes. Quasi-sensitive attributes are not sensitive by themselves, but certain values or their combinations may ...
Pu Shi, Li Xiong, Benjamin C. M. Fung
EDM
2008
117views Data Mining» more  EDM 2008»
13 years 9 months ago
Integrating Knowledge Gained From Data Mining With Pedagogical Knowledge
Abstract. Discovering knowledge from raw data is one of the goals of data mining. Yet, it is not always clear how this knowledge is used in educational computing systems and how ex...
Roland Hübscher, Sadhana Puntambekar