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Received:June 30, 2014 Revised:August 08, 2014
Received:June 30, 2014 Revised:August 08, 2014
中文摘要: 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.
Abstract: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.
keywords: electric power business systems data preprocessing sequential pattern mining function optimization
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王成现,胡扬波,谭晶.Apriori-Based算法改进在电力业务系统功能优化中的应用.计算机系统应用,2015,24(3):183-187
WANG Cheng-Xian,HU Yang-Bo,TAN Jing.Improved Apriori-Based Algorithm Application to the Electric Power Business System Function Optimization.COMPUTER SYSTEMS APPLICATIONS,2015,24(3):183-187
王成现,胡扬波,谭晶.Apriori-Based算法改进在电力业务系统功能优化中的应用.计算机系统应用,2015,24(3):183-187
WANG Cheng-Xian,HU Yang-Bo,TAN Jing.Improved Apriori-Based Algorithm Application to the Electric Power Business System Function Optimization.COMPUTER SYSTEMS APPLICATIONS,2015,24(3):183-187
