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Real-time stream mining: online knowledge extraction using classifier networks

机译:实时流挖掘:使用分类器网络进行在线知识提取

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摘要

The world is increasingly information-driven. Vast amounts of data are being produced by different sources and in diverse formats. It is becoming critical to endow assessment systems with the ability to process streaming information from sensors in real time in order to better manage physical systems, derive informed decisions, tweak production processes, and optimize logistics choices. This article first surveys the works dealing with building, adapting, and managing networks of classifiers, then describes the challenges and limitations of the current approaches, discusses possible directions to deal with these limitations, and presents some open research questions that need to be investigated.
机译:世界越来越受到信息驱动。不同来源和不同格式正在产生大量数据。赋予评估系统实时处理来自传感器的流信息以更好地管理物理系统,得出明智的决定,调整生产流程并优化物流选择的能力变得至关重要。本文首先调查了有关构建,调整和管理分类器网络的工作,然后描述了当前方法的挑战和局限性,讨论了解决这些局限性的可能方向,并提出了一些需要研究的开放性研究问题。

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