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SIGMOD
2006
ACM
219views Database» more  SIGMOD 2006»
16 years 6 months ago
Modeling skew in data streams
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, rela...
Flip Korn, S. Muthukrishnan, Yihua Wu
SIGCOMM
2010
ACM
15 years 6 months ago
Cloudward bound: planning for beneficial migration of enterprise applications to the cloud
In this paper, we tackle challenges in migrating enterprise services into hybrid cloud-based deployments, where enterprise operations are partly hosted on-premise and partly in th...
Mohammad Y. Hajjat, Xin Sun, Yu-Wei Eric Sung, Dav...
148
Voted
AINA
2008
IEEE
15 years 8 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...
174
Voted
KDD
1998
ACM
123views Data Mining» more  KDD 1998»
15 years 11 months ago
Scaling Clustering Algorithms to Large Databases
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Paul S. Bradley, Usama M. Fayyad, Cory Reina
CIKM
2010
Springer
15 years 5 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