Process mining aims to obtain insights on business processes from event logs, using algorithms to:
- automatically discover models
- check certain rules and regulations
- project performance on process models.
Process mining techniques typically only deal with the control flow: that is, which process steps are being executed for a particular case and in what order.
Our industry partners are often interested in, and pose questions on, the interplay between process and data. These questions include:
- Do gold customers get a different treatment than silver customers?
- Are there behavioural indicators that correlate with high customer satisfaction?
- Can we predict deviations to the prescribed behaviour based on other data?
- Does the process behaviour of customers differ based on the channel through which they initiated contact (email, front desk, call centre ..)?
Current support for answering such questions is very limited. Therefore, in this project, we aim to answer them combining data mining and process mining techniques.
In this project, we aim to develop new process mining techniques to handle the data available in event logs.
We'll undertake a small literature scan of major categories of process mining and data mining techniques. After this, we'll develop new techniques and potentially evaluate them on real data from our industry partners.
Depending on your level of study, focus might be on one or more of these activities.
All of the mentioned research activities are on the edge of current scientific knowledge. Therefore, we expect to publish the performed research in top conferences and journal articles.
We also expect to implement prototypes of the developed techniques.
Skills and experience
To be considered for this projects, you'll need to be familiar with basic programming and have in-depth knowledge of either:
- business process management (IFN515/IAB203/IAB320 or similar)
- in-depth knowledge of data mining
It is also recommended, but not mandatory, that you're familiar with:
- process mining (IFN650/IAB321)
- basic data mining techniques.
You may be able to apply for a research scholarship in our annual scholarship round.
Contact the supervisor for more information.