Applying Process Mining to Predict Customer Behavior and Recommend Actions

Background In the Dutch health care system health care insurance is obligated for all residents. The government sets the basis package and insurers compete based on price and service. Customer service is therefore very important for every health insurance company; especially in the fast changing digital world. As a result customer satisfaction is the most Read More …

Certif-AI

Certif-AI: Certification of production process quality through Artificial Intelligence Description Production processes can be made ‘smarter’ by exploiting the data streams that are generated by the machines that are used in production. In particular these data streams can be mined to build a model of the production process as it was really executed – as Read More …

The Certif-AI project has been approved by NWO

A new PhD position will become available in the PA group to develop and evaluate techniques for mining production processes from sensor data. This PhD position will be funded by NWO on the approved Certif-AI (Certification of production process quality through Artificial Intelligence) project. Below, is a short description for this project. Production processes can Read More …

Process mining for six sigma: a guideline and tool support

Graafmans, T. L. F., Türetken, O., Poppelaars, J. J. G. H., & Fahland, D. (Accepted/In press). Process mining for six sigma: a guideline and tool support. Business & Information Systems Engineering. Abstract Process mining offers a set of techniques for gaining data-based insights into business processes from event logs. The literature acknowledges the potential benefits Read More …

BPI Challenge 2020

The tenth International Business Process Intelligence Challenge is again co-located with ICPM. This challenge provides participants with a real-life event log, and challenges them to analyze these data using whatever techniques available, focusing on one or more of the process owner’s questions or proving other unique insights into the process(es) captured in the event log. Read More …

Run 6 of “Process Mining in Healthcare” MOOC starts on April 13th, 2020

On April 13, 2020, the sixth run of the free FutureLearn online course ‘Process mining in healthcare’ will start, register now! We are happy to be able to run this course again, after over 2,500 students registered for the first three runs. Healthcare in particular has come under increasing pressure to reduce cost while improving Read More …

Run 12 of “Introduction to Process Mining with ProM” MOOC starts at April 13, 2020

On April 13, 2020, the twelfth run of the free FutureLearn online course ‘Introduction to process mining with ProM’ will start. Join the 15.000 students who enrolled before you and join the course! Process mining is a novel collection of techniques that connects the areas of data science and business process management. Using process mining Read More …

Working on Process Mining? Consider becoming a member of the IEEE Task Force on Process Mining!

If you did not join the IEEE Task Force on Process Mining yet, please consider doing so!                 >> register via https://www.tf-pm.org/subscription/form  << The IEEE Task Force on Process Mining (TFPM) was established in October 2009 as part of the IEEE Computational Intelligence Society. The set of activities and members has expanded over the last Read More …

Two new PhD students: Eva Klijn and Fatemeh Shafiee

On February 1st, Eva Klijn and Fatemeh Shafiee started working as PhD students in the PA group. Eva started as PhD-TA, and is supervised by Dirk Fahland. Fatemeh started as a PhD student on the TACTICS project, and is supervised by Natalia Sidorova. A big welcome to the both of them!

Enabling efficient process mining on large data sets: realizing an in-database process mining operator

Dijkman, R., Gao, J., Syamsiyah, A., van Dongen, B., Grefen, P., & ter Hofstede, A. (2019). Enabling efficient process mining on large data sets: realizing an in-database process mining operator. Distributed and Parallel Databases, 38(1), 227-253. https://doi.org/10.1007/s10619-019-07270-1 Abstract Process mining can be used to analyze business processes based on logs of their execution. These execution Read More …