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» Co-Scheduling of Computation and Data on Computer Clusters
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LOCA
2007
Springer
14 years 4 months ago
Inferring the Everyday Task Capabilities of Locations
Abstract. People rapidly learn the capabilities of a new location, without observing every service and product. Instead they map a few observations to familiar clusters of capabili...
Patricia Shanahan, William G. Griswold
ICDM
2003
IEEE
134views Data Mining» more  ICDM 2003»
14 years 3 months ago
Probabilistic User Behavior Models
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
Eren Manavoglu, Dmitry Pavlov, C. Lee Giles
SAINT
2003
IEEE
14 years 3 months ago
Extracting Spatial Knowledge from the Web
The content of the world-wide web is pervaded by information of a geographical or spatial nature, particularly such location information as addresses, postal codes, and telephone ...
Yasuhiko Morimoto, Masaki Aono, Michael E. Houle, ...
ICAC
2006
IEEE
14 years 4 months ago
Learning Application Models for Utility Resource Planning
Abstract— Shared computing utilities allocate compute, network, and storage resources to competing applications on demand. An awareness of the demands and behaviors of the hosted...
Piyush Shivam, Shivnath Babu, Jeffrey S. Chase
ICDE
2010
IEEE
227views Database» more  ICDE 2010»
14 years 5 months ago
Incorporating partitioning and parallel plans into the SCOPE optimizer
— Massive data analysis on large clusters presents new opportunities and challenges for query optimization. Data partitioning is crucial to performance in this environment. Howev...
Jingren Zhou, Per-Åke Larson, Ronnie Chaiken