High-Level Event Mining: Overview and Future Work

TL;DR

This paper reviews high-level event mining, which extends process analysis from individual low-level events to system-wide phenomena, addressing complex issues like bottlenecks and congestion.

Contribution

It provides an extensive overview of existing methods and challenges in elevating process mining from event-level to system-level analysis.

Findings

Highlights the importance of system-level event analysis

Identifies key challenges in high-level event mining

Summarizes current approaches and future research directions

Abstract

Process mining traditionally relies on input consisting of low-level events that capture individual activities, such as filling out a form or processing a product. However, many of the complex problems inherent in processes, such as bottlenecks and compliance issues, extend beyond the scope of individual events and process instances. Consider congestion, for instance, it can involve and impact numerous cases, much like how a traffic jam affects many cars simultaneously. High-level event mining seeks to address such phenomena using the regular event data available. This report offers an extensive and comprehensive overview at existing work and challenges encountered when lifting the perspective from individual events and cases to system-level events.