摘要
为了满足企业业务流程模型的运行效率、完善网上购物流程,提出了一种基于Petri网行为轮廓的网上购物流程挖掘方法.首先根据某网上购物系统提供的事件日志,利用Petri网行为轮廓的弱序关系,设计出相应的流程模型;然后通过计算模型与事件日志之间的服从程度,对初始模型进行改进和优化;最后用实例分析说明了本文挖掘方法的可行性.
In order to meet the operational efficiency of the enterprise business process model and improve the online shopping process,an online shopping process mining method based on behavioral profile of Petri net is proposed.Firstly,according to the event log provided by an online shopping system,the corresponding process model is designed by using the weak order relationship of the behavioral profile of Petri net.Then the degree of compliance between the model and the event log is calculated,and the initial model is improved and optimized.The last example analysis shows that the algorithm has feasibility.
作者
王倩倩
王丽丽
WANG Qianqian;WANG Lili(College of Mathematics and Big Data,Anhui University of Science and Technology,Huainan 232001,China)
出处
《延边大学学报（自然科学版）》
CAS
2019年第1期75-79,共5页
Journal of Yanbian University（Natural Science Edition）
基金
国家自然科学基金资助项目(61402011
61572035)
安徽省高校自然科学基金资助重点项目(KJ2016A208)
关键词
流程挖掘
行为轮廓
服从性
process mining
behavioral profile
compliance
