关键词: 过程挖掘, 遗传挖掘算法, 控制流维度, 组织维度, 执行者过程树

Abstract: There are a large number of events exist in event logs that contain activities of both order and originators,also named organizational dimension information.Control flow discovery algorithms can automatically construct the control flow process model from the event log,and the organization discovery algorithm builds a social network.If two dimensions can be combined and displayed in a model,a more complete process organization view can be provided,which is helpful for processing and organization analysis.Therefore,a DoubleDimensional Genetic Process Mining Method based on Executor Process Tree (BdSm) was proposed.Inductive miner was used to prepare a highquality initial population for genetic mining algorithm,which could generate high-quality control flow dimension process models.A measurement of distance between activities based on the similarity of executor was proposed.The process model of control flow was extended by organizational dimension information,and a double-dimensional process model based on the executor process tree was generated.The simulation logs and four open event logs were used to verify BdSm,and the results showed that BdSm could generate a process model of highly comprehensive quality in the control flow dimension.Meanwhile,typically working models and organizational structures could be found through organizational dimension information.

Key words: process mining, genetic mining algorithm, control flow dimension, organizational dimension, executor process tree