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» Approximate data mining in very large relational data
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ICDM
2006
IEEE
124views Data Mining» more  ICDM 2006»
15 years 10 months ago
Finding "Who Is Talking to Whom" in VoIP Networks via Progressive Stream Clustering
Technologies that use the Internet network to deliver voice communications have the potential to reduce costs and improve access to communications services around the world. Howev...
Olivier Verscheure, Michail Vlachos, Aris Anagnost...
AUSDM
2008
Springer
367views Data Mining» more  AUSDM 2008»
15 years 6 months ago
Categorical Proportional Difference: A Feature Selection Method for Text Categorization
Supervised text categorization is a machine learning task where a predefined category label is automatically assigned to a previously unlabelled document based upon characteristic...
Mondelle Simeon, Robert J. Hilderman
SDM
2012
SIAM
297views Data Mining» more  SDM 2012»
13 years 6 months ago
A Flexible Open-Source Toolbox for Scalable Complex Graph Analysis
The Knowledge Discovery Toolbox (KDT) enables domain experts to perform complex analyses of huge datasets on supercomputers using a high-level language without grappling with the ...
Adam Lugowski, David M. Alber, Aydin Buluç,...
GIS
1995
ACM
15 years 8 months ago
Collaborative Spatial Decision Making with Qualitative Constraints
: Usually spatial planning problems involve a large number of decision makers with different backgrounds and interests. The process of Collaborative Spatial Decision Making (CSDM)...
Nikos I. Karacapilidis, Dimitris Papadias, Max J. ...
ICPP
2005
IEEE
15 years 10 months ago
Filter Decomposition for Supporting Coarse-Grained Pipelined Parallelism
We consider the filter decomposition problem in supporting coarse-grained pipelined parallelism. This form of parallelism is suitable for data-driven applications in scenarios wh...
Wei Du, Gagan Agrawal