Study On The Application Of Data Mining Based On Police Information

Now, the public security systems have had the rich service information resources. These information resources not only are the buried treasure of the public security work, but also have enormous social and economic values. At present, most public security management information systems stay at a low level, which just serve as records management, service query, static statistics and etc. Thus, the information resources available can't be fully used for people have ignored the values of information resources, let alone provide some methods such as information mining, data analysis. Therefore, the situation can't meet the current need for public security work. There may be some implicit, inherent relationships among information that likely are knowledge. It is urgent to find, extract knowledge or rules and exploit them. Data mining technologies have been researched in many fields, but just have primarily been researched and applied to the public security work. This thesis focuses on how to apply data mining technologies to the public security work, how to analyze the public security information, then provide a variety of knowledge to leaders and management department, support them to analyze, discover and know the trends and regulations of the public security, furthermore to support decision making and reference according to the in-time statistics.It's well known that the society is developing rapidly and the relations between people are adjusted correspondingly. A variety of conflicts and interest dispute increase the criminal rate. There are a lot of factors which lead to crime, but which are major factors and which minor. The thesis takes advantages of the data mining technologies to analyze the really causes for some subsequences.The thesis applies two methods of data mining to carry on the example structure and obtains the related model. One is decision tree ID3 algorithm. ID3 algorithm is used to classify the criminal causes, which consider the entropies of all attributes and reduce various unreasonable selective divisions. ID3 algorithm tends to select those...