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Toward Managing Uncertain Spatial Information for Situational Awareness Applications

机译:致力于为情境意识应用程序管理不确定的空间信息

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Situational awareness (SA) applications monitor the real world and the entities therein to support tasks such as rapid decision-making, reasoning, and analysis. Raw input about unfolding events may arrive from variety of sources in the form of sensor data, video streams, human observations, and so on, from which events of interest are extracted. Location is one of the most important attributes of events, useful for a variety of SA tasks. In this article, we consider the problem of reaching situation awareness from textual input. We propose an approach to probabilistically model and represent (potentially uncertain) event locations described by human reporters in the form of free text. We analyze several types of spatial queries of interest in SA applications. We design techniques to store and index the models, to support the efficient processing of queries. Our extensive experimental evaluation over real and synthetic datasets demonstrates the effectiveness and efficiency of our approaches.
机译:情境感知(SA)应用程序监视现实世界及其中的实体,以支持诸如快速决策,推理和分析之类的任务。关于展开事件的原始输入可能以传感器数据,视频流,人类观察等形式从各种来源获得,从中提取感兴趣的事件。位置是事件的最重要属性之一,对于各种SA任务很有用。在本文中,我们考虑了通过文本输入达到情境意识的问题。我们提出一种概率模型的方法,并以自由文本的形式表示(由潜在的不确定性)人类记者描述的事件位置。我们分析了SA应用程序中感兴趣的几种类型的空间查询。我们设计存储和索引模型的技术,以支持查询的有效处理。我们对真实和合成数据集进行的广泛实验评估证明了我们方法的有效性和效率。

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