Extraction of Missing Tendency Using Decision Tree Learning in Business Process Event Log

Hiroki Horita, Yuta Kurihashi, Nozomi Miyamori
2020 Data  
In recent years, process mining has been attracting attention as an effective method for improving business operations by analyzing event logs that record what is done in business processes. The event log may contain missing data due to technical or human error, and if the data are missing, the analysis results will be inadequate. Traditional methods mainly use prediction completion when there are missing values, but accurate completion is not always possible. In this paper, we propose a method
more » ... for understanding the tendency of missing values in the event log using decision tree learning without supplementing the missing values. We conducted experiments using data from the incident management system and confirmed the effectiveness of our method.
doi:10.3390/data5030082 fatcat:q7hswyier5c35pva5dgprcccxe