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Discover and visualize association rules from sensor observations on the web

机译:通过网络上的传感器观察发现并可视化关联规则

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摘要

Nowadays, Web-based applications has became a common practice in environment monitoring. These applications provide open platforms for users to discover access and integrate near real-time sensor data which is collected from distributed sensors and sensor networks. To make use of the shared sensor data on the Web, conceptual models in a particular domain are normally adopted. However, most conceptual models require high quality data and high level domain knowledge. Such limitations greatly limit the application of these models. To overcome some of these limitations, this paper proposes a data-mining approach to analyze patterns and relationships among different sensor data sets. This approach provides a flexible way for users to understand hidden relationships in shared sensor data, and can help them to make use Web-based sensor systems better.
机译:如今,基于Web的应用程序已成为环境监视中的一种普遍做法。这些应用程序为用户提供了开放的平台,以供用户发现访问权限并集成从分布式传感器和传感器网络收集的近实时传感器数据。为了利用Web上共享的传感器数据,通常采用特定领域中的概念模型。但是,大多数概念模型都需要高质量的数据和高级领域知识。这样的限制极大地限制了这些模型的应用。为了克服这些局限性,本文提出了一种数据挖掘方法来分析不同传感器数据集之间的模式和关系。这种方法为用户提供了一种灵活的方式来理解共享传感器数据中的隐藏关系,并可以帮助他们更好地利用基于Web的传感器系统。

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