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VLDB
1997
ACM
175views Database» more  VLDB 1997»
15 years 10 months ago
STING: A Statistical Information Grid Approach to Spatial Data Mining
Spatial data mining, i.e., discovery of interesting characteristics and patterns that may implicitly exist in spatial databases, is a challenging task due to the huge amounts of s...
Wei Wang 0010, Jiong Yang, Richard R. Muntz
IADIS
2008
15 years 8 months ago
Data Mining In Marketing Acquisition CAMPAIGNS
Business applications of data mining in marketing often focus on use of predictive models to classify customer events such as acquisition, sales of products and services or custom...
Krzysztof Dzieciolowski, Dennis Kira
ICDM
2010
IEEE
99views Data Mining» more  ICDM 2010»
15 years 4 months ago
A System for Mining Temporal Physiological Data Streams for Advanced Prognostic Decision Support
We present a mining system that can predict the future health status of the patient using the temporal trajectories of health status of a set of similar patients. The main noveltie...
Jimeng Sun, Daby Sow, Jianying Hu, Shahram Ebadoll...
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
15 years 8 months ago
Practical Private Computation and Zero-Knowledge Tools for Privacy-Preserving Distributed Data Mining
In this paper we explore private computation built on vector addition and its applications in privacypreserving data mining. Vector addition is a surprisingly general tool for imp...
Yitao Duan, John F. Canny
FGCS
2007
160views more  FGCS 2007»
15 years 6 months ago
Distributed data mining in grid computing environments
The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Distributed Data Mining (DDM), calls for the support of a powerful Grid with an e...
Ping Luo, Kevin Lü, Zhongzhi Shi, Qing He