In process mining there exist mainly three categories of analysis:
- (1) process discovery, which deals with the reconstruction of a process model from an event log,
- (2) conformance checking, which checks if the reality conforms to the desired way of executing the process, and
- (3) enhancement, which enriches process models with additional information.
All three analysis categories support an analyst finding issues in a process using data-centric techniques.
We offer various topics around the research area of process mining, including but not limited to:
- Process learning: using machine learning models (i.e., deep learning) to better capture how a process has been really executed.
- Automatic analysis recommendations: analyzing an event log such that the system provides potential insights to the analyst automatically for further (manual) analysis.
- Visual exploration: extending visual data analysis techniques to allow better and high-quality insights extraction from large data sets.
- Task mining: grouping low level activities that people, machines, or organizations execute within a process to allow detailed analysis of the specific tasks.
Feel free to contact us, if you are interested in one of the topic or in process mining in general for a bachelor / master thesis.
- Good programming skills
- (depends) data mining, machine learning, deep learning
- Interest and enthusiasm in the analysis of event data from processes and algorithmic challenges