Reference: AIR-BAGEL: An Interactive Root cause-Based Anomaly Generator for Event Logs,
Jonghyeon Ko, Jongyup Lee, and Marco Comuzzi, Proceedings of International Conference on Process Mining (ICPM) Demo Track, 2020, Accepted for publication (Sep 2020)
AIR-BAGEL is a tool to generate pseudo-real trace-level anomalies in event logs. Anomalies to be injected are defined by their root cause, i.e., resource behaviour or system malfunctioning. For each root cause, several anomaly types can be specified, e.g., deleting, replacing or moving events in a trace. Root causes and anomalies have been modelled based on existing literature on event log cleaning and data quality analysis. AIR-BAGEL addresses the issue of unavailability of labelled real world event logs for developing and evaluating event log cleaning and reconstruction techniques and it represents a step forward compared to current approaches in the literature that simply inject different types of anomalies randomly in event logs.
- Python - version 3.6+
- tk/tkinter
- Python Imaging Libary
- PM4Py
See the tutorial document airbagel-tutorial.pdf.
Project is: in progress
Created by Jonghyeon Ko (whd1gus2@unist.ac.kr), Jungyup Lee (belllight@unist.ac.kr) and Marco Comuzzi (mcomuzzi@unist.ac.kr). We are part of the Intelligent Enterprise Lab (iel.unist.ac.kr) at the Department of Industrial Engineering, UNIST (Ulsan, Republic of Korea). Feel free to contact if you have any question!