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» Mining time-changing data streams
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CIKM
2010
Springer
13 years 6 months ago
Partial drift detection using a rule induction framework
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Damon Sotoudeh, Aijun An
ICDE
2011
IEEE
235views Database» more  ICDE 2011»
12 years 11 months ago
Fast data analytics with FPGAs
—The rapidly increasing amount of data available for real-time analysis (i.e., so-called operational business intelligence) is creating an interesting opportunity for creative ap...
Louis Woods, Gustavo Alonso
ICDE
2002
IEEE
204views Database» more  ICDE 2002»
14 years 9 months ago
Approximating a Data Stream for Querying and Estimation: Algorithms and Performance Evaluation
Obtaining fast and good quality approximations to data distributions is a problem of central interest to database management. A variety of popular database applications including,...
Sudipto Guha, Nick Koudas
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
14 years 8 months ago
GraphScope: parameter-free mining of large time-evolving graphs
How can we find communities in dynamic networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity timepoints in ...
Jimeng Sun, Christos Faloutsos, Spiros Papadimitri...
ICDM
2003
IEEE
125views Data Mining» more  ICDM 2003»
14 years 25 days ago
Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns
The data stream captured by recording inhabitantdevice interactions in an environment can be mined to discover significant patterns, which an intelligent agent could use to automa...
Edwin O. Heierman III, Diane J. Cook