Context-based Distributed Regression in Virtual Organizations

The characteristics of virtual organizations present significant challenges to both distributed data mining methods within a metalearning framework and statistical multi-level models. Using hierarchical models, this paper explicitly address the context heterogeneity existing across the partners of virtual organizations. Two new approaches of context-based distributed data mining are analyzed and compared with traditional meta-learning based distributed data mining technique on both simulation and real-world data sets.

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