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» An overview of clustering methods
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108
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CLOUD
2010
ACM
15 years 5 months ago
Comet: batched stream processing for data intensive distributed computing
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...
116
Voted
EDBT
2009
ACM
166views Database» more  EDBT 2009»
15 years 5 months ago
Neighbor-based pattern detection for windows over streaming data
The discovery of complex patterns such as clusters, outliers, and associations from huge volumes of streaming data has been recognized as critical for many domains. However, patte...
Di Yang, Elke A. Rundensteiner, Matthew O. Ward
GIS
2009
ACM
15 years 5 months ago
REG^2: a regional regression framework for geo-referenced datasets
Traditional regression analysis derives global relationships between variables and neglects spatial variations in variables. Hence they lack the ability to systematically discover...
Oner Ulvi Celepcikay, Christoph F. Eick
ASPLOS
1996
ACM
15 years 4 months ago
Shasta: A Low Overhead, Software-Only Approach for Supporting Fine-Grain Shared Memory
This paper describes Shasta, a system that supports a shared address space in software on clusters of computers with physically distributed memory. A unique aspect of Shasta compa...
Daniel J. Scales, Kourosh Gharachorloo, Chandramoh...
133
Voted
VISSYM
2003
15 years 1 months ago
Visual Hierarchical Dimension Reduction for Exploration of High Dimensional Datasets
Traditional visualization techniques for multidimensional data sets, such as parallel coordinates, glyphs, and scatterplot matrices, do not scale well to high numbers of dimension...
Jing Yang, Matthew O. Ward, Elke A. Rundensteiner,...