Design And Implementation Of Public Security Intelligence Information Management System Based On Data Minin

With the rapid development of information technology and the progress of data mining technology,many industries have established electronic information management platforms.For the public security information management,a large amount of information data will be generated every day.The huge workload leads to the phenomenon of delayed and false information from time to time,which has an adverse impact on the information management of public security.Therefore,it is considered to design and develop a set of public security information management system to manage information an analyze data,so as to improve the standardization,security and scientificity of information,management.This dissertation divides functional modules of the system according to the project requirements,including reporting information management module,information collection equipment management module,information data management module,information statistics and analysis module and general function module.In the report information management module,the pixel diffusion algorithm is used to encrypt the report image;POI technology is used in the information collection equipment management module to realize equipment batch registration;In the information data management module,the text similarity algorithm based on editing distance is used to optimize the shortcomings of the traditional search methods;In the intelligence data statistics and analysis module,the intelligence data are counted through the Echarts visual chart,and the intelligence aggregation area is extracted by using the clustering algorithm,so as to provide reference for the work of police personnel;Redis technology is used in the general fuction module to cache image verification codes and notification announcements.Finally,the system is comprehensively tested to ensure that the system meets the on-line operation conditions.To solve the problem of information aggregation region extraction,this dissertation intends to use two clustering algorithms: K-means++ algorithm based on distance and DBSCAN algorithm based on desity.Through the comparison and analysis of experiments,it is concluded that DBSCAN algorithm is more suitable for the project scenario,and then the selection of its parameters is optimized to obtain a parameter adaptive DBSCAN algorithm to solve the problems that are difficult to be determined by the parameters of DBSCAN algorithm,in addition,the clustering algorithm is applied to this project.This system helps to enhance the public security’s ability of information management and analysis,meanwhile,improve the work efficiency of public security police officers.The research results will have certain practical significance in public security information management.