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ISMIS
2005
Springer
15 years 12 months ago
Using Supervised Clustering to Enhance Classifiers
Abstract. This paper centers on a novel data mining technique we term supervised clustering. Unlike traditional clustering, supervised clustering is applied to classified examples ...
Christoph F. Eick, Nidal M. Zeidat
KDD
2006
ACM
130views Data Mining» more  KDD 2006»
16 years 6 months ago
Efficient anonymity-preserving data collection
The output of a data mining algorithm is only as good as its inputs, and individuals are often unwilling to provide accurate data about sensitive topics such as medical history an...
Justin Brickell, Vitaly Shmatikov
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
16 years 6 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
COMPSAC
2004
IEEE
15 years 10 months ago
Hiding Sensitive Patterns in Association Rules Mining
Data mining techniques have been developed in many applications. However, it also causes a threat to privacy. We investigate to find an appropriate balance between a need for priv...
Guanling Lee, Chien-Yu Chang, Arbee L. P. Chen
SDM
2012
SIAM
261views Data Mining» more  SDM 2012»
13 years 8 months ago
Combining Active Learning and Dynamic Dimensionality Reduction
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
Mustafa Bilgic