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ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
16 years 18 days ago
Incremental Subspace Clustering over Multiple Data Streams
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Qi Zhang, Jinze Liu, Wei Wang 0010
SSD
2005
Springer
173views Database» more  SSD 2005»
15 years 11 months ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras
PAKDD
2004
ACM
121views Data Mining» more  PAKDD 2004»
15 years 11 months ago
Secure Association Rule Sharing
Abstract. The sharing of association rules is often beneficial in industry, but requires privacy safeguards. One may decide to disclose only part of the knowledge and conceal stra...
Stanley R. M. Oliveira, Osmar R. Zaïane, Y&uu...
ICDM
2003
IEEE
111views Data Mining» more  ICDM 2003»
15 years 11 months ago
OP-Cluster: Clustering by Tendency in High Dimensional Space
Clustering is the process of grouping a set of objects into classes of similar objects. Because of unknownness of the hidden patterns in the data sets, the definition of similari...
Jinze Liu, Wei Wang 0010
ICDM
2003
IEEE
134views Data Mining» more  ICDM 2003»
15 years 11 months ago
Probabilistic User Behavior Models
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
Eren Manavoglu, Dmitry Pavlov, C. Lee Giles