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» Optimal randomization for privacy preserving data mining
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KDD
2004
ACM
158views Data Mining» more  KDD 2004»
14 years 8 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
ICDM
2005
IEEE
188views Data Mining» more  ICDM 2005»
14 years 1 months ago
Hierarchy-Regularized Latent Semantic Indexing
Organizing textual documents into a hierarchical taxonomy is a common practice in knowledge management. Beside textual features, the hierarchical structure of directories reflect...
Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, V...
CIKM
2009
Springer
14 years 2 months ago
Privacy-enhanced public view for social graphs
We consider the problem of releasing a limited public view of a sensitive graph which reveals at least k edges per node. We are motivated by Facebook’s public search listings, w...
Hyoungshick Kim, Joseph Bonneau
ICICS
2005
Springer
14 years 1 months ago
Private Itemset Support Counting
Private itemset support counting (PISC) is a basic building block of various privacy-preserving data mining algorithms. Briefly, in PISC, Client wants to know the support of her i...
Sven Laur, Helger Lipmaa, Taneli Mielikäinen
SDM
2010
SIAM
183views Data Mining» more  SDM 2010»
13 years 9 months ago
GraSS: Graph Structure Summarization
Large graph databases are commonly collected and analyzed in numerous domains. For reasons related to either space efficiency or for privacy protection (e.g., in the case of socia...
Kristen LeFevre, Evimaria Terzi