Modeling and reasoning about uncertainty in context-aware systems

Binh An Truong, Young-Koo Lee, Sungyoung Lee
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引用次数: 45

Abstract

Uncertainty always exists as an unavoidable factor when developing context-aware applications for pervasive computing environments. In this paper, we propose a unified context model to support representation and reasoning about uncertain context. Our unified context model extends the existing, de-facto ontology-based context models with probabilistic models to support probabilistic reasoning. Especially, our context model can be easily integrated with existing ontology-based context-aware systems. Given the unified context model, unified context ontology can be built and used as frameworks in developing context aware applications. Besides, our recipe of supporting the probabilistic reasoning is flexible and adaptive to the highly variable features of pervasive computing environments
上下文感知系统中不确定性的建模和推理
在为普适计算环境开发上下文感知应用程序时,不确定性始终是一个不可避免的因素。在本文中,我们提出了一个统一的上下文模型来支持不确定上下文的表示和推理。我们的统一上下文模型使用概率模型扩展了现有的基于事实本体的上下文模型,以支持概率推理。特别是,我们的上下文模型可以很容易地与现有的基于本体的上下文感知系统集成。有了统一的上下文模型,就可以建立统一的上下文本体,并将其作为框架用于开发上下文感知应用程序。此外,我们支持概率推理的方法是灵活的,可以适应普适计算环境的高度可变特征
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