Distributed Data Mining: The JAM system architecture

Andreas L. Prodromidis, Salvatore Stolfo, Shelley Tselepis, Terrance Truta, Jeffrey Sherwin & David Kalina
This paper describes the system architecture of JAM (Java Agents for Meta-learning), a distributed data mining system that scales up to large and physically separated data sets. An earlyversion of the JAM system was described in Stolfo-et-al-97-KDD-JAM. Since then, JAM has evolved both architecturally and functionally and here we present the final design and implementation details of this system architecture. JAM is an extensible agent-based distributed data mining system that supports the remote dispatch and...
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