摘要
提出一种针对电力业务系统功能优化算法.首先,从Web服务器和客户端采集用户日志数据;然后,对用户日志数据进行预处理,并将事务数据集转换为序列数据库;最后,采用改进的Apriori-based算法发现紧耦合的功能模块,进行功能之间的优化组合,提升业务人员的工作效率.实验表明该方法在揭示业务功能模块的耦合性方面的有效性.
This paper proposes an algorithm for electric power business system function optimization. Firstly we extract log data from the Web server and the client user. Then, we preprocess the user log dataset, and convert transaction dataset into a sequence data. Finally, we use the improved Apriori-based algorithm to find tight coupling function modules, and make optimization combination between the functions to improve the working efficiency of the business. Experiments show that the method is effective in revealing the coupling of the business function module.
出处
《计算机系统应用》
2015年第3期183-187,共5页
Computer Systems & Applications
关键词
电力业务系统
数据预处理
序列模式挖掘
功能优化
electric power business systems
data preprocessing
sequential pattern mining
function optimization
