移动数据挖掘的杂波自适应可视化

Brett Gillick, Hasnain AlTaiar, S. Krishnaswamy, J. Liono, Nicholas Nicoloudis, Abhijat Sinha, A. Zaslavsky, M. Gaber
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引用次数: 9

摘要

移动设备上的实时数据流分析正成为人们关注的焦点。虽然近年来开发了许多移动数据流挖掘算法,但尚未出现通用的可扩展可视化技术。本文展示了我们创新的移动设备自适应集群可视化技术。我们已经在谷歌Android平台上完全实现了这项技术,并提供了不同数据集的演示:位置(真实的和合成的)和股票市场(真实的)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clutter-Adaptive Visualization for Mobile Data Mining
There is an emerging focus on real-time data stream analysis on mobile devices. While many mobile data stream mining algorithms have been developed in recent times, generic and scalable visualization techniques have not been presented. This paper presents the demonstration of our innovative clutter-adaptive cluster visualization technique for mobile devices. We have fully implemented this technique on the Google Android platform and provide demonstrations for different datasets: location (both real and synthetic), and stock-market (real).
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