流程挖掘在银行服务管理中的应用  

The application of process mining to bank service management

作　　者：卢盛祺[1,2,3] 李远刚[1,2] 管连 周赟[3] 

机构地区：[1]上海财经大学信息管理与工程学院,上海200433 [2]上海财经大学上海市金融信息技术重点实验室,上海200433 [3]复旦大学软件学院,上海200433 [4]国际商业机器(中国)有限公司,北京100101

出　　处：《微型机与应用》2016年第18期88-92,共5页Microcomputer & Its Applications

基　　金：国家自然科学基金(71271126);教育部博士点专项科研基金(20120078110002)

摘　　要：随着银行服务信息化的不断发展,银行面临如何从大量的服务数据中提取有价值的信息用以提升服务效率的问题。在银行服务管理系统的实际应用中,由于其业务具有并发性事件多、日志数量大等特点,选择并行Apriori算法进行分析。与传统的Apriori算法相比,针对银行业务中并发性业务较多的特点,设计使用了并行Apriori算法,解决了单服务器运行效率随日志数量明显下降的弊端。银行服务管理系统每日会产生大量流程的日志数据,记录每一位参与员工的工作状态,通过调用并行Aporiori算法,挖掘服务流程日志中的关联规则,找出能够高效协作的员工组合。实验结果表明,将并行Apriori算法应用于服务流程日志的关联规则挖掘,使系统可以根据规则将协作关系紧密的员工分配在一起共同处理服务请求,提高了服务效率,取得了合理的应用效果,提高了银行服务管理系统中服务分配的智能。With the development of bank service information,the bank faces the problem how to extract valuable information from a large amount of service data to help banks improve service efficiency. In the practical use of the management systems of banks,because of its specialty of having lots of concurrency operation and producing many event logs,we choose the parallel association algorithm to analyze the process of bank management. Compared with the traditional Apriori algorithm,this paper uses the parallel algorithm given that the bank management system has many concurrency operations. As a result,it solves the problem that the efficiency of system declines rapidly with the increase of the number of event logs. Management systems of the bank generate much log data to record bank's staff work every day. In this paper,the parallel Apriori algorithm is applied to find association rules in the service process log to identify efficient team of employees. As a result,this algorithm improves the efficiency of bank service.

关 键 词：流程挖掘 关联规则 员工组合 组织优化 并行Apriori算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]