一个集成空间上下文模型和空间推理算法的API

M. Kjærgaard
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引用次数: 3

摘要

上下文感知应用程序与空间上下文模型的集成通常使用公共查询语言完成。然而,对空间上下文信息进行估计和推理的算法可以从更紧密的集成中受益。面向对象的API使这种集成成为可能,并有助于降低算法的复杂性,使其更易于维护和开发。本文提出了一种面向对象的物理环境上下文模型API,并对一种称为几何空间树的位置建模方法进行了扩展,为位置建模提供了充分的支持。API的效用在室内定位系统的几个实际案例中进行了评估,并涵盖了几种类型的空间推理算法
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An API for integrating spatial context models with spatial reasoning algorithms
The integration of context-aware applications with spatial context models is often done using a common query language. However, algorithms that estimate and reason about spatial context information can benefit from a tighter integration. An object-oriented API makes such integration possible and can help reduce the complexity of algorithms making them easier to maintain and develop. This paper propose an object-oriented API for context models of the physical environment and extensions to a location modeling approach called geometric space trees for it to provide adequate support for location modeling. The utility of the API is evaluated in several real-world cases from an indoor location system, and spans several types of spatial reasoning algorithms
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