Process Mining (VL/UE)
Prof. Dr. Matthias Weidlich
Content
One emerging branch of data science is process mining. In the field of process automation, process mining aims at deriving qualitative and quantitative insights on the execution of a process based on recorded events logs.
Structure
In the first part of the course, lectures and recitations will focus on the formal foundations and basic techniques of process mining. That includes algorithms for process discovery (constructing models from event data), conformance checking (identifying deviations between models and event data), and model extension (enriching models based on event data). The recitations will include a tutorial in which the students are exposed to real-world data and process mining tools.
The second part of the course will be organised as a seminar. Each student will be asked to read a recent research paper on process mining (selection from a given list) and give a critical assessment of the approach presented in the paper in the form of a 45min presentation.
The course will be given in English. The first lecture will take place on Thursday, 20th October, 2016.
Exam
There will be an oral exam at the end of the semester. To be eligible to take the exam, each student will be required to give a presentation (45min) on a research paper in the second part of the course.
Exams will take place at the following dates:
- 20.02.2017
- 21.02.2017
- 01.03.2017
- 02.03.2017
- 18.04.2017
For each date, there are six slots available (some time between 9:00 and 13:00). Registration for one of these slots needs to happen between 16.01.2017 and 06.02.2017 and is handled by Ms Bah (RUD 25, room 4.402).
Credit Points
The course counts for 5 LP and is open for: Informatik, Master of Science (M.Sc.) Informatik, Master of Education (M.Ed.) Wirtschaftsinformatik, Master of Science (M.Sc.). The related area of specialisation is "Daten- und Wissensmanagement".
Guest Lecture
On January 19, 2017, there will be a guest lecture by Rami Eid-Sabbagh of Lana-Labs on the application of conformance checking in industry projects. (tutorial slides)
Dates
VL | Do 9-11 | RUD 26, Raum 1'303 |
UE | Do 11-13 | RUD 26, Raum 1'303 |
Lecture Slides
- Lecture 1 - Context
- Lecture 2 - Event Logs
- Lecture 3 - Alpha
- Lecture 4 - Heuristic Miner
- Lecture 5 - Inductive Miner
- Presentation by M. Itzerott
- Lecture 6 - Evaluation
- Lecture 7 - Conformance
- Lecture 8 - Alignments
- Lecture 9 - Enhancement
Recitations
- Assignment Sheet 1 - Behavioural Formalisms
- Assignment Sheet 2 - Event Logs
- Assignment Sheet 3 - Alpha
- Assignment Sheet 4 - Heuristic Miner
- Assignment Sheet 5 - Process Trees
- Assignment Sheet 6 - Inductive Miner
- Assignment Sheet 7 - Measures
- Assignment Sheet 8 - Conformance
- Assignment Sheet 9 - Alignments
Presentation Slots
Date | Topic and Presenters |
---|---|
December 8, 2016 |
3) Genetic Mining |
|
4) Discovery based on Regions Emma Hennig and Lukas Abegg |
|
8) Discovery of Roles Belhassen Ouerghi and Tugce Aksel |
December 15, 2016 |
7) Artifact-based Discovery Thuy-Vi Vo and Marina Serpinskaya |
|
9) Stream-based Discovery Michael Aringer and Matthias Menzel |
|
|
February 2, 2017 |
6) Handling Duplicated Tasks Matthias Becher and Markus Richter |
|
13) Alternative Measures for Model Precision Vanessa Chanliau and Dmytro Fradin |
|
16) Temporal Anomaly Detection Nargiz Bakhshaliyeva and David Rodriguez Edel |
|
|
February 9, 2017 |
17) Queue Mining Stephan Fahrenkrog-Petersen and Hermann Stolte |
|
18) Predictive Monitoring Valentin Zambelli and Simon Remy |
|
19) Sequence Encodings in Predictive Monitoring Carl Tramburg and Kamarhulrhizwan Benjamin Jaidi |
Presentation Topics
Note on the dates: topics 1-9 are likely to be scheduled for December 8 or December 15, 2016. The remaining topics will be presented in February 2017.
Josep Carmona, Jordi Cortadella, Michael Kishinevsky: A Region-Based Algorithm for Discovering Petri Nets from Event Logs. BPM 2008: 358-373 paper link
See AGNES for further details:
- M.Sc. 3313071 (VL) and 3313072 (UE)