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» Data Mining for Intrusion Detection: Techniques, Application...
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BIBM
2007
IEEE
159views Bioinformatics» more  BIBM 2007»
15 years 7 months ago
Predicting Future High-Cost Patients: A Real-World Risk Modeling Application
Health care data from patients in the Arizona Health Care Cost Containment System, Arizona’s Medicaid program, provides a unique opportunity to exploit state-of-the-art data pro...
Sai T. Moturu, William G. Johnson, Huan Liu
INFORMATICALT
2008
196views more  INFORMATICALT 2008»
15 years 17 days ago
An Efficient and Sensitive Decision Tree Approach to Mining Concept-Drifting Data Streams
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang
121
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ESANN
2004
15 years 2 months ago
Neural networks for data mining: constrains and open problems
When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
Razvan Andonie, Boris Kovalerchuk
94
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ICDM
2008
IEEE
142views Data Mining» more  ICDM 2008»
15 years 7 months ago
Clustering Events on Streams Using Complex Context Information
Monitoring applications play an increasingly important role in many domains. They detect events in monitored systems and take actions such as invoke a program or notify an adminis...
YongChul Kwon, Wing Yee Lee, Magdalena Balazinska,...
103
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IJVR
2008
106views more  IJVR 2008»
15 years 17 days ago
Improved View Frustum Culling Technique for Real-Time Virtual Heritage Application
Real-time virtual heritage application is normally executed with a high performance computer system. This is due to the complexity and highly computational cost which makes such sy...
Mohd Shahrizal Sunar, Abdullah Mohd Zin, Tengku M....