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PODS
2003
ACM
143views Database» more  PODS 2003»
14 years 7 months ago
Maintaining variance and k-medians over data stream windows
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
Brian Babcock, Mayur Datar, Rajeev Motwani, Liadan...
ICEBE
2005
IEEE
168views Business» more  ICEBE 2005»
14 years 1 months ago
Frequency Operators for Condensative Queries over Data Streams
Over a traditional Database Management System (DBMS), the answer to an aggregate query is usually much smaller than the answer to a similar nonaggregate query. Therefore, we call ...
Lisha Ma, Werner Nutt
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
14 years 1 months 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
ISAAC
2004
Springer
117views Algorithms» more  ISAAC 2004»
14 years 26 days ago
Adaptive Spatial Partitioning for Multidimensional Data Streams
We propose a space-efficient scheme for summarizing multidimensional data streams. Our sketch can be used to solve spatial versions of several classical data stream queries effici...
John Hershberger, Nisheeth Shrivastava, Subhash Su...
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
14 years 2 days ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...