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» Providing k-anonymity in data mining
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KDD
2008
ACM
119views Data Mining» more  KDD 2008»
15 years 10 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
JUCS
2010
164views more  JUCS 2010»
14 years 8 months ago
On Sustainability of Context-Aware Services Among Heterogeneous Smart Spaces
Abstract: Most of ambient intelligence studies have tried to employ inductive methods (e.g., data mining) to discover useful information and patterns from data streams on sensor ne...
Jason J. Jung
EDBT
2011
ACM
225views Database» more  EDBT 2011»
14 years 1 months ago
SeMiTri: a framework for semantic annotation of heterogeneous trajectories
GPS devices allow recording the movement track of the moving object they are attached to. This data typically consists of a stream of spatio-temporal (x,y,t) points. For applicati...
Zhixian Yan, Dipanjan Chakraborty, Christine Paren...
SIGMOD
2004
ACM
140views Database» more  SIGMOD 2004»
15 years 10 months ago
Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Corrine Cheng, Jörg Sander, Samer Nassar
MINENET
2006
ACM
15 years 4 months ago
Privacy-preserving performance measurements
Internet performance is an issue of great interest, but it is not trivial to measure. A number of commercial companies try to measure this, as does RIPE, and many individual Inter...
Matthew Roughan, Yin Zhang