Automatic derivation of context descriptions

Christian Jung, Denis Feth, Yehia Elrakaiby
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引用次数: 5

Abstract

Context-awareness in mobile information systems bears a huge potential. However, context-awareness is still in its infancy and its full potential is not yet exploited. One reason is the poorly supported creation and learning of suitable context descriptions. Another problem is the questionable predictive power of context descriptions that makes it difficult to correctly determine the current user context. For applications that depend on the user context, the reliable determination of the context is essential. In this paper, we propose a process to characterize contexts. We correlate raw contextual information with user activities to determine accurate context descriptions. In a case study, we show how different statistical methods can be used to determine correlations, and analyze their applicability.
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上下文描述的自动派生
上下文感知在移动信息系统中具有巨大的潜力。然而,上下文感知仍处于起步阶段,其全部潜力尚未得到开发。一个原因是缺乏对创建和学习合适的上下文描述的支持。另一个问题是上下文描述的预测能力存在问题,这使得正确确定当前用户上下文变得困难。对于依赖于用户上下文的应用程序,可靠地确定上下文是必不可少的。在本文中,我们提出了一个表征上下文的过程。我们将原始上下文信息与用户活动关联起来,以确定准确的上下文描述。在一个案例研究中,我们展示了如何使用不同的统计方法来确定相关性,并分析它们的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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