EMADS: An extendible multi-agent data miner

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摘要

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.

论文关键词:Multi-agent data mining (MADM),Classifier generation

论文评审过程:Available online 9 January 2009.

论文官网地址:https://doi.org/10.1016/j.knosys.2008.10.009