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RWTH Process Mining Lecture 7: Quality of Discovered Models and Representations
Prof.dr.ir. Wil van der Aalst (www.vdaalst.com, @wvdaalst)
In this lecture, Wil van der Aalst discusses notions such as fitness/recall, precision, simplicity, and generalization. These are used to reason about the quality of discovered process models. The second part focuses on the representation bias and prepares for the more advanced notions used later.
More about this Process Mining Course @ RWTH Aachen University (BPI 2021):
This course consists of around 20 lectures covering the different fields of process mining, including five process discovery techniques, three conformance checking techniques, data preparation, decision mining, predictive analytics, machine learning, big-data analytics, and process mining software. The course is at an introductory level, but also comprehensive and providing details on state-of-the-art process mining techniques.
The videos are part of the Business Process Intelligence (BPI) course organized by the PADS (Process and Data Science) group at RWTH (www.pads.rwth-aachen.de) led by prof.dr.ir. Wil van der Aalst. The lectures by Wil van der Aalst are online due to COVID-19 and recorded in Spring 2021. Niklas Adams, Bianka Bakullari, Ali Norouzifar, Marco Pegoraro, Mahsa Pourbafrani, Mahnaz Qafari, Majid Rafiei, and Miriam Wagner took care of the instructions and assignments.
For more information, visit and
Enjoy the course! We hope it will inspire you to dive deeper into the wonderful world of process mining.
1 Introduction to Process Mining
2 Decision Trees
3 Association Rules & Clustering
4 Introduction to Process Discovery
5 Petri Nets & Alpha Algorithm
6 Alpha Algorithm Continued
7 Quality of Discovered Models and Representations
8 Heuristic Mining
9 Region-Based Mining
10 Inductive Mining
11 Event Data and Exploration
12 Conformance Checking (1/2)
13 Conformance Checking (2/2)
14 Decision Mining
15 Organizational Mining & Bottleneck Analysis
16 Refined Process Mining Framework and Operational Support
17 Dealing with Big Event Data
18 Discussion of an old/possible exam
19 Summary of the Course and Next Steps
See for all lectures in this course. See for last year’s course (BPI 2020) and for an Introduction to Data Science (IDS 20/21).