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Analyzing the Acquisition and Management of Context

机译：分析上下文的获取和管理

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摘要

Mobile users want mobile services tailored to their current context and needs. These context-aware services have primarily focused on position information; using other types of user information would enhance the development of smarter services. There is a range of frameworks that manage and distribute user context; however, when several information sources and inference techniques are available, these context frameworks face the need to make appropriate decisions to facilitate the most suitable context information to applications. This article describes strategies to solve a context acquisition problem, namely the choice of the information channel, given available user information and context obtaining services. The proposed context acquisition strategy, based on Bayesian decision theory, improves the frameworks' decision making and enables integrating and encapsulating a wide set of context inference and reasoning algorithms and data sources, in a well-documented, transparent, and principled way.
机译：移动用户希望根据其当前环境和需求量身定制移动服务。这些上下文感知服务主要集中在位置信息上。使用其他类型的用户信息将增强智能服务的开发。有多种框架可以管理和分发用户上下文。但是，当有几种信息源和推理技术可用时，这些上下文框架将面临做出适当决策的需要，以便为应用程序提供最合适的上下文信息。本文介绍解决上下文获取问题的策略，即在给定可用的用户信息和上下文获取服务的情况下选择信息通道。所提出的基于贝叶斯决策理论的上下文获取策略，改进了框架的决策，并能够以有据可查，透明且原则化的方式集成和封装各种上下文推理和推理算法以及数据源。

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