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» Data Stream Clustering: Challenges and Issues
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CCGRID
2009
IEEE
14 years 12 hour ago
Performance Issues in Parallelizing Data-Intensive Applications on a Multi-core Cluster
The deluge of available data for analysis demands the need to scale the performance of data mining implementations. With the current architectural trends, one of the major challen...
Vignesh T. Ravi, Gagan Agrawal
ICDM
2009
IEEE
167views Data Mining» more  ICDM 2009»
13 years 3 months ago
Self-Adaptive Anytime Stream Clustering
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
ICDE
2008
IEEE
157views Database» more  ICDE 2008»
14 years 6 months ago
Approximate Clustering on Distributed Data Streams
Abstract-- We investigate the problem of clustering on distributed data streams. In particular, we consider the k-median clustering on stream data arriving at distributed sites whi...
Qi Zhang, Jinze Liu, Wei Wang 0010
CCGRID
2008
IEEE
13 years 11 months ago
Data Management Challenges of Data-Intensive Scientific Workflows
Scientific workflows play an important role in today’s science. Many disciplines rely on workflow technologies to orchestrate the execution of thousands of computational tasks. ...
Ewa Deelman, Ann L. Chervenak
AINA
2008
IEEE
13 years 7 months ago
A Communication-Efficient Distributed Clustering Algorithm for Sensor Networks
Sensor networks usually generate continuous stream of data over time. Clustering sensor data as a core task of mining sensor data plays an essential role in analytical application...
Amirhosein Taherkordi, Reza Mohammadi, Frank Elias...