The Research Of Data Mining And Its Application In Exit-entry Administration

Data Mining is currently one of the most popular and promising fields in the research area of Artificial Intelligence. With China's rapid economic development and its entry of WTO, international communication between countries become more frequent than ever, among which effective and efficient exit-entry administration plays a very important role. By investigating the popular technologies and methodologies on data mining, this paper introduces some of their comparatively mature models in the field of exit-entry administration and explores some specific algorithms in details. In the meantime, we have also presented some relative Data Mining methods and analyze how to apply them to solve specific real-world challenge problems such as intelligent management on exit-entry administration.The main content of this paper can be summarized in the following three aspects:1. The paper employs rough set algorithm to seek for similarities in the records of output labor force, simplifies the data by knowledge reduction, and then generate the corresponding rules. Finally the experimental result in the practice work has been further discussed.2. By taking advantage of Decision Tree theory to analyze the records of criminals who commit crimes in Hong Kong and Macao, we construct a preliminary crime alerting model to find out the potential regulation and inclination which can lead to irregularity, the relationship between the different criminalities, and the connection of specific state and certainly criminalities.3. The classical algorithm of association rule, Apriori, in exit-entry administration, has been introduced in this paper and made some improvement in order to find some "interesting" knowledge beneficial for our daily administration work.