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Challenges for Context Management Systems Imposed by Context Inference

机译:上下文推断对上下文管理系统的挑战

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This work gives an overview over the challenges for context management systems in Ubiquitous Computing frameworks or Personal Smart Spaces. Focused on the integration of context inference in today's context management systems (CMSs) we address important design decisions for future frameworks. The inference system we have in mind is probabilistic and relies on the concept of Bayeslets, special inference rules extending Bayesian networks. We show that for inference rule creation, storage, inference scheduling and update frequency the best solutions are hybrid, allowing for high flexibility and performance while reducing resource costs. We also see that human expert knowledge cannot be substituted completely in an efficient context-aware system.
机译:这项工作概述了普适计算框架或个人智能空间中的上下文管理系统所面临的挑战。着重于在当今的上下文管理系统(CMS)中集成上下文推断,我们针对未来框架提出了重要的设计决策。我们想到的推理系统是概率性的,并且依赖于贝叶斯概念,即扩展贝叶斯网络的特殊推理规则。我们证明,对于推理规则的创建,存储,推理调度和更新频率,最佳解决方案是混合的,从而在降低资源成本的同时提供了高度的灵活性和性能。我们还看到,在高效的情境感知系统中不能完全替代人类专家知识。

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