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» Applying Grid Technologies to Distributed Data Mining
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FGCS
2000
143views more  FGCS 2000»
13 years 7 months ago
A data intensive distributed computing architecture for "Grid" applications
Modern scientific computing involves organizing, moving, visualizing, and analyzing massive amounts of data from around the world, as well as employing large-scale computation. The...
Brian Tierney, William E. Johnston, Jason Lee, Mar...
DEXAW
2007
IEEE
128views Database» more  DEXAW 2007»
13 years 12 months ago
Sharing Data on the Grid using Ontologies and distributed SPARQL Queries
The vision of the Semantic Web is to make Web content machine-readable. To describe data, the Resource Description Framework has been extended with a schema-level and description ...
Andreas Langegger, Martin Blöchl, Wolfram W&o...
ESCIENCE
2007
IEEE
14 years 2 months ago
Community Training: Partitioning Schemes in Good Shape for Federated Data Grids
In federated Data Grids, individual institutions share their data sets within a community to enable collaborative data analysis. Data access needs to be provided in a scalable fas...
Tobias Scholl, Richard Kuntschke, Angelika Reiser,...
IJIIDS
2008
201views more  IJIIDS 2008»
13 years 8 months ago
MALEF: Framework for distributed machine learning and data mining
: Growing importance of distributed data mining techniques has recently attracted attention of researchers in multiagent domain. Several agent-based application have been already c...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek, S...
PPOPP
2005
ACM
14 years 1 months ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...