EMADS: An extendible multi-agent data miner

نویسندگان

  • Kamal Ali Albashiri
  • Frans Coenen
  • Paul H. Leng
چکیده

In this paper we describe EMADS, an Extendible Multi-Agent Data mining System. The EMADS vision is that of a community of data mining agents, contributed by many individuals, interacting under decentralised control to address data mining requests. EMADS is seen both as an end user application and a research tool. This paper details the EMADS vision, the associated conceptual framework and the current implementation. Although EMADS may be applied to many data mining tasks; the study described here, for the sake of brevity, concentrates on agent based data classification. A full description of EMADS is presented.

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عنوان ژورنال:
  • Knowl.-Based Syst.

دوره 22  شماره 

صفحات  -

تاریخ انتشار 2009