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» Privacy Preserving Clustering by Data Transformation
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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 8 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
DKE
2010
167views more  DKE 2010»
13 years 5 months ago
Discovering private trajectories using background information
Trajectories are spatio-temporal traces of moving objects which contain valuable information to be harvested by spatio-temporal data mining techniques. Applications like city traf...
Emre Kaplan, Thomas Brochmann Pedersen, Erkay Sava...
SDM
2010
SIAM
115views Data Mining» more  SDM 2010»
13 years 9 months ago
Reconstructing Randomized Social Networks
In social networks, nodes correspond to entities and edges to links between them. In most of the cases, nodes are also associated with a set of features. Noise, missing values or ...
Niko Vuokko, Evimaria Terzi
SAC
2010
ACM
14 years 27 days ago
User-controlled generalization boundaries for p-sensitive k-anonymity
Numerous privacy models based on the k-anonymity property have been introduced in the last few years. While differing in their methods and quality of their results, they all focus...
Alina Campan, Traian Marius Truta, Nicholas Cooper
JIIS
2006
113views more  JIIS 2006»
13 years 7 months ago
Spatial ordering and encoding for geographic data mining and visualization
: Geographic information (e.g., locations, networks, and nearest neighbors) are unique and different from other aspatial attributes (e.g., population, sales, or income). It is a ch...
Diansheng Guo, Mark Gahegan