基于k-means和肘部法则的业务流程聚类方法

Business Process Clustering Method Based on k-means and Elbow Method

流程挖掘是从实际业务执行日志出发,提取结构化流程信息的过程。流程挖掘技术现已广泛应用于现实业务流程的发现和辅助建模,并能够通过差异分析的方法帮助改进已有业务流程。提出一种基于聚类的流程挖掘方法,首先从事件日志出发,对基于活动的流程路径进行描述,然后对基于距离的活动视图感知的路径聚类,通过聚类结果分析流程特征,为流程变更提供决策。以现实的会议注册系统作为实验对象,论证了方法的有效性。该方法可为流程变更提供决策支持。

Process mining is to extract structured process information from the actual business event log.Process mining technology is now widely used in the process discovery and assisted modeling of real business processes,and can help to improve existing business processes through differential analysis.This paper proposed a cluster-based process mining method.Firstly,it described the activity-based process pathway starting from the event log,then analyzed the pathway clustering of the active view awareness based on distance,and analyzed the characteristics of process through the clustering results.These can provide decision making for process change.This paper took the actual conference registration system as the experimental object,demonstrated the effectiveness of the proposed method,it provides support for decision making for process modification.