RWTH Process Mining Lecture 8: Heuristic Mining

RWTH Process Mining Lecture 8: Heuristic Mining

In this lecture, Wil van der Aalst presents the first process discovery technique able to deal with concurrency, noise, incompleteness, OR-splits/joins, skipping, etc. The heuristic mining technique uses two steps: first, a dependency graph is created and then a causal net. The latter can be converted into BPMN or a Petri net.

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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.

Enjoy the course! We hope it will inspire you to dive deeper into the wonderful world of process mining.

Overview
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

Twitter: #processmining @wvdaalst

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What software/package do you use to draw the causal net on your slides? Thank you!