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本文在动态社会信息网络的形式化表达与建模基础上,结合事件本身具有的突发性、破坏性、公共性、紧迫性、连带性、不确定性等特性,从多属性约束的角度,提出了一种基于大数据的公共安全事件检测方法。通过本方法能够对社会公共安全大数据视频、文字进行数据自动分析。待检测到公共安全事件后,采用影响违法犯罪人的理性选择,减少被害要因及条件,增强关护力和群众安全感等手段,实现对被检事件的有效防控。
Based on the formal expression and modeling of dynamic social information network, combining with the characteristics of suddenness, destructiveness, publicity, urgency, associatedness and uncertainty of the event itself, from the perspective of multi-attribute constraints, A method based on big data for detecting public safety events is proposed. Through this method, we can analyze the data of social public safety big data video and text automatically. To be detected after the public safety incidents, the adoption of the rational choice of criminals, to reduce the causes and conditions of injury, and enhance the security forces and the masses such as means to achieve effective control of the seizure.