Design And Implementation Of The Self-service Equipment Operating Officer Platform Based On Data Mining

Since the 1980 s,the world economy rapid development,has played an important role in the financial sector.China's banking sector is established taking shape in thirty years the basic framework of the financial data communication network,the basic realization of the mass concentration of business data processing and unified management,preliminary set up customer oriented service information processing system of the bank.Since it was founded in 1984,the development of A bank is always accompanied by the progress of science and technology,the remarkable honor behind is the strong support of informationization construction.Wave with the development of Banks electronic,information,in order to guarantee the standardization of 7 * 24 hours service,self-service equipment has been widely used in banking,for business development has played A more and more A big push.With the wide use of self-service equipment,A bank faces more problems and challenges,how to go to the understanding of all aspects of self-service equipment running status,how to evaluate the contribution degree of self-service equipment,how to maximize the strengths of self-service equipment and function is the key.A bank self-service equipment management of the operating system as A bank-wide,after many years of practice,formed the mature self-service equipment management framework,through technology and management methods,continuously improve the self-help equipment control measures,promote hard control ability,better promote the development of the business of selling.But A bank self-service equipment operation management system still exists the lack of A unified global integrity management planning,the lack of self-service equipment operation management situation analysis and unified view of wanda group,failure risk eventmonitoring is not comprehensive,lack of interdisciplinary assessment of active defense,self-help equipment operation management information security tool types and the severity phenomenon of trivializes situated less problems,failed to truly meet the needs of business development at A deeper level.To cope with the intensified competition of banking industry,this article is based on data mining and other related theory,establishes a set of systematic and comprehensive,dynamic,coherent self-service equipment operation management platform.Implementation of selling self-help equipment operation situation,event monitoring of the unified management and disposal,analysis and display,enterprise business as the core,the large-scale operation and business data association,analysis and mining effectively,the real-time fault detection equipment,intelligent data analysis and monitoring of visualization,continuous risk identification equipment,a comprehensive grasp business operational control present situation,provide platform for selling self-help equipment support personnel,to provide decision basis for business development,build for the future high capacity,fast expand,flexible,and controllable,clustered deployment of new channels of self-help service platform.Based on the mining based clustering algorithm in-depth analysis of the data,using hierarchical clustering and K-statistical classification mean trading amount of self-service equipment across the province to form a trading method,self-service equipment model,experimental design and the use of G bank self-service equipment of the province's 16 cities the average monthly trading volume data set as test data verify the analysis.Finally,using new technology of distributed architecture,a distributed cache implementation through the Java language and the production operation system.Running results show that the system preliminary realizes the continuous identification of commercial bank self-service equipment,data acquisition,event monitoring and maintaining control,promote A bank self-service equipment operation management continuously improve and perfect,provide decision-making basis for business development.