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Uncertainty handling in semantic reasoning for accurate context understanding

机译:语义推理中的不确定性处理,用于准确的上下文理解

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摘要

Context aware systems are using various sensing technologies in order to recognize end-users situations; however these technologies are vulnerable to hardware failures, energy depletion, communication problems and multiple other issues. This generates an uncertainty about the events received from the sensors, which is translated into a confidence given to these events. This confidence is used in the context-aware reasoning through a fusion of sensor data to make more accurate decisions. In this paper, we focus on handling uncertainty in sensor-based context aware applications and we propose a method for the measurement of uncertainty based on both physical and operational behaviors of the sensors. We describe how the level of uncertainty is incorporated into different layers of a semantically driven context aware system and how it is transferred to a decision engine in order to perform more accurate decisions in ambiguous observations. (C) 2015 Elsevier B.V. All rights reserved.
机译:情境感知系统正在使用各种传感技术来识别最终用户的情况。但是,这些技术易受硬件故障,能量消耗,通信问题和其他多种问题的影响。这产生了关于从传感器接收到的事件的不确定性,该不确定性转化为对这些事件的置信度。通过融合传感器数据以做出更准确的决策,在上下文感知推理中使用此置信度。在本文中,我们专注于处理基于传感器的上下文感知应用程序中的不确定性,并且我们提出了一种基于传感器的物理和操作行为的不确定性测量方法。我们描述了如何将不确定性的级别合并到语义驱动的上下文感知系统的不同层中,以及如何将其转移到决策引擎,以便在不确定的观察中执行更准确的决策。 (C)2015 Elsevier B.V.保留所有权利。

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