泛在数据流挖掘中数据元素模糊分类的可视化

Brett Gillick, S. Krishnaswamy, M. Gaber, A. Zaslavsky
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引用次数: 7

摘要

泛在数据挖掘(UDM)允许使用资源有限的设备在连续数据流上执行数据挖掘操作。可视化是帮助用户理解和解释数据挖掘结果并帮助用户指导进一步挖掘操作的基本工具。然而,目前还没有在线实时可视化工具来补充UDM算法。在本文中,我们研究了可视化技术的使用,在一个在线实时可视化框架内,以增强手持设备上的UDM结果解释。我们展示了一个概念实现的证明,用于可视化数据元素对使用模糊逻辑算法产生的集群的隶属度。
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Visualisation of Fuzzy Classification of Data Elements in Ubiquitous Data Stream Mining
Ubiquitous data mining (UDM) allows data mining operations to be performed on continuous data streams using resource limited devices. Visualisation is an essential tool to assist users in understanding and interpreting data mining results and to aide the user in directing further mining operations. However, there are currently no on-line real-time visualisation tools to complement the UDM algorithms. In this paper we investigate the use of visualisation techniques, within an on-line real-time visualisation framework, in order to enhance UDM result interpretation on handheld devices. We demonstrate a proof of concept implementation for visualising degree of membership of data elements to clusters produced using fuzzy logic algorithms.
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