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目前,警务情报的运作主要依靠侦查员在犯罪调查中对信息的搜集、理解和加工,这项工作往往漫长而又耗费精力。本文提出了一种警务情报分析框架(PLAF)的实现方式,该框架能够自动处理从目击者陈述中提取的信息,以识别事件中的实体,为警察勤务提供一个完整、准确的情境图,进而提高态势感知并支持决策过程。本文概述了处理情报信息所面对的困难,着重研究了处理这些困难所应用的方法,总结了用于案发后警务分析系统方面的理论综述。最后,本文运用一个实际的警务调查案例来演示该系统的运用过程。
At present, police intelligence operations mainly depend on investigators collecting, comprehending and processing information in criminal investigations. This work is often lengthy and laborious. This paper presents a PLPS implementation that automatically processes the information extracted from eyewitness statements to identify entities in the incident and provide a complete and accurate situational picture of police service, Thereby increasing situational awareness and supporting the decision-making process. This article outlines the difficulties in handling intelligence information, focuses on methods used to deal with these difficulties, and summarizes the theoretical overview used in post-incident policing systems. Finally, this article uses an actual police investigation case to demonstrate the system’s operation.