关键词: 业务流程, 异常检测, 机器学习, 日志记录, 工作流

Abstract: Thanks to the advantages of workflow in logical information organization and collaborative work,it has been widely used in various industries in recent years.Business process,the most typical workflow,perform a series of activities to produce products or services and generate value for clients.However,In the execution of the business process,anomaly and exceptions may disturb the business process and pose risks for the process goals.Therefore,it is necessary to predict and find anomalies in advance during business process execution and make adjustments as soon as possible.For this reason,an anomaly detection method based on machine learning algorithms was proposed,which utilized the process execution logs and activity execution durations to predict the process time constraint violations and process behavior anomaly in real time.With experiments conducted on real-life business process logs,the method proposed could effectively identify the processes potentially violating time constraint and the processes with abnormal behavior.

Key words: business process, anomaly detection, machine learning, logs, workflow