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首页> 外文会议>Ground/air multisensor interoperability, integration, and networking for persistent ISR V >Agile Sensor Tasking for CoIST using Natural Language Knowledge Representation and Reasoning
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Agile Sensor Tasking for CoIST using Natural Language Knowledge Representation and Reasoning

机译：使用自然语言知识表示和推理的CoIST敏捷传感器任务分配

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摘要

We describe a system architecture aimed at supporting Intelligence, Surveillance, and Reconnaissance (ISR) activities in a Company Intelligence Support Team (CoIST) using natural language-based knowledge representation and reasoning, and semantic matching of mission tasks to ISR assets. We illustrate an application of the architecture using a High Value Target (HVT) surveillance scenario which demonstrates semi-automated matching and assignment of appropriate ISR assets based on information coming in from existing sensors and human patrols operating in an area of interest and encountering a potential HVT vehicle. We highlight a number of key components of the system but focus mainly on the human/machine conversational interaction involving soldiers on the field providing input in natural language via spoken voice to a mobile device, which is then processed to machine-processable Controlled Natural Language (CNL) and confirmed with the soldier. The system also supports CoIST analysts obtaining real-time situation awareness on the unfolding events through fused CNL information via tools available at the Command and Control (C2). The system demonstrates various modes of operation including: automatic task assignment following inference of new high-importance information, as well as semi-automatic processing, providing the CoIST analyst with situation awareness information relevant to the area of operation.
机译：我们使用基于自然语言的知识表示和推理，以及任务任务与ISR资产的语义匹配，描述了旨在支持公司情报支持团队（CoIST）中的情报，监视和侦察（ISR）活动的系统体系结构。我们使用高价值目标（HVT）监视方案说明了该架构的应用，该方案演示了半自动匹配和分配适当的ISR资产的基础，这些情报是基于在感兴趣区域中进行操作并遇到潜在威胁的现有传感器和人类巡逻来的信息HVT车辆。我们重点介绍了该系统的许多关键组件，但主要集中在人/机对话交互上，涉及在现场的士兵通过语音向移动设备提供自然语言输入，然后将其处理为机器可处理的受控自然语言（ CNL），并与士兵确认。该系统还支持CoIST分析人员通过Command and Control（C2）上可用的工具通过融合的CNL信息获得有关展开事件的实时情况意识。该系统演示了多种操作模式，包括：根据新的重要信息推断出自动任务，以及半自动处理，为CoIST分析师提供了与操作领域相关的态势感知信息。

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