PEM4PPM: A Cognitive Perspective on the Process of Process Mining
Journal
Lecture Notes in Computer Science
Type
conference contribution
Date Issued
2023-09
Author(s)
Abstract
During the last decades, process mining (PM) has matured and rapidly increased in its adoption. Making sense of data is a main part of the work of PM analysts, which involves cognitive processes. Recent work has leveraged behavioral data to explain these processes. Still, the process of process mining (PPM) is yet to be well understood and a theoretical foundation for explaining how these processes unfold is missing. This paper attempts to fill this gap by understanding how PPM data can be analyzed in a theory-guided manner and what insights can be gained from this analysis. To investigate these aspects, we analyzed verbal data and interaction traces obtained from analysis sessions with 29 participants performing a PM task. The analysis was based on the Predictive Processing (PP) theory and the derived Prediction Error Minimization (PEM) process, anchored in cognitive science. The results include (1) a theoretical adaptation of the PEM theory to the PPM context, (2) four strategies utilized by PM analysts, identified, and validated based on the adapted theory, and (3) an understanding of the differences in performance between analysts using different strategies and independence of the expertise level and the strategy choice.
Language
English
Keywords
Process Mining
Predictive Processing
Prediction Error Minimization
Analysis Strategies
Mixed Methods
HSG Classification
contribution to scientific community
Refereed
Yes
Book title
Business Process Management (BPM 2023)
Volume
14159
Start page
465
End page
481
Division(s)
File(s)![Thumbnail Image]()
Name
PEM4PPM A Cognitive Perspective on the Process of Process Mining.pdf
Size
481.93 KB
Format
Adobe PDF
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