The Correlation Research Of Emergency Based On Electronic Footprint Data

In recent years the frequent occurring of public security events has leaded a serious damage to the masses’ life and property.Facing the massive and diverse structured internet electronic footprint data,extracting events attributes and mining events correlation have a great promotion effect on the enhancement of the event control and prevention,which event correlation model construction and platform construction are involved.We have finished the following in this paper:1、Construct the events correlation analysis ontology model.According to the concept mapping from real world to cyber world,this paper proposes domain objective and domain task flow.Extends the Upper ontology using ontology theory to construct domain ontology model.In the meantime,this paper analyzes and defines the calculators involved in the correlation mining.2、Show specific approaches of emergency correlation analysis and prediction.Based on 2 kind electronic footprints,using correlation analysis and multi time series analysis methods,this paper mines the propagation factors and the trigger relation of the events of same category and different categories to do the prediction of the numbers of events happening.3、Design the share platform structure of emergency events.Based on internet footprint data,this paper analyzes platform business model and role model,and design the platform technical framework and part of the system API,propose configurable concurrent task framework and automatic data immigration framework,which provides huge convenience and flexibility of data immigration and disposing.This paper deeply explores the emergency correlation mining domain which was involved less in the previous research,proposes the emergency correlation analysis model based on electronic footprint data and show an example to verify the model and construct the platform of emergency,which lays the foundation of improving events transparency and provides a new idea and a practical operation platform for the prevention and control of public security events.