A generic and extendible Multi-Agent Data Mining (MADM) framework, EMADS (the Extendible Multi-Agent Data mining System) is described. The central feature of the framework is that it avoids the use of agreed meta-language formats by supporting a system of wrappers. The advantage offered is that the system is easily extendible, so that further data agents and mining agents can simply be added to the system. A demonstration EMADS framework is currently available. The paper includes details of the EMADS architecture and the wrapper principle incorporated into it. A full description and evaluation of the framework's operation is provided by considering two MADM scenarios. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Albashiri, K. A., & Coenen, F. (2009). A generic and extendible multi-agent data mining framework. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5572 LNAI, pp. 203–210). https://doi.org/10.1007/978-3-642-02319-4_24
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