Selected Topics in Process Mining

 

Organisational Information

• Coordinator: Lisa Mannel
• The registration is carried out via the central registration process on the web site SUPRA maintained by the Computer Science Department.
• This seminar is held in English (all written reports and presentations will be in English).

Kick-off meeting

Only the students who will participate in the seminar will be contacted and they will be provided with the kick-off meeting date and time. All deadlines for submission of outline, term paper, presentation slides will be announced in the kick-off meeting. Presentations will take place on probably two or three days and this will also be announced in the kick-off meeting.

Seminar Details

Process mining is a novel scientific discipline on the interface between process models and event data. Process mining techniques are used to discover, analyze and improve real processes by extracting knowledge from event logs. The main challenge lies in turning event data "Big Data" into valuable information related to process performance and compliance. We can use process mining results in order to identify and understand bottlenecks, inefficiencies, and deviations.

This seminar focuses on current research topics in advanced areas of process mining techniques which can be used to discover and analyze real processes, when event logs and processes become larger and more complex. In particular, conformance checking, one of the main research areas in process mining, aims at comparing the modeled behavior and the observed behavior in order to find commonalities and deviations between them and to measure the severity of such deviations. Conformance checking plays an important role not only for researchers and data scientists in process-oriented data science, but also for data and business analysts aiming at finding deviations and improving processes in companies. This seminar deals with challenges in applicability and characteristics of process mining techniques, such as conformance checking techniques, applicable to large and complex datasets.

Concept

Each student is assigned a research topic and will

• do a literature survey
• write an outline of his/her research paper
• write his/her own research paper based on the given topic
• give a presentation, and
• participate in all presentation meetings and discussions

The goal is to make students not only read and understand research papers, but also write a research paper on their own, generate research ideas, and make a presentation in an understandable, clear way for the audience.

Please note that all details regarding this seminar will be announced in the kick-off meeting, including the topics and deadlines for each task.

Registration

The registration is carried out via the central registration process on the web site SUPRA maintained by the Computer Science Department.

In order to increase your chance for being elected for this seminar, please state your qualifications, experiences, and all grades in your enrolled study as detailed as possible. Please give clearly why you are definitely a suitable candidate for this seminar.

You will be informed about the first meeting in the weeks after SUPRA announces the final participation lists.

Prerequisites

Basic knowledge of Computer Science and very good, solid mathematical background needed (e.g. set theory, logic, automata etc.). Prior knowledge in process mining, process discovery, conformance checking, e.g., lecture Business Process Intelligence (BPI) required.

Furthermore, the following prerequisites are highly recommended:

• Successful participation in the Introduction to Data Science (IDS) course
• Successful participation in the Business Process Intelligence (BPI) course
• Successful participation in the "Process Mining: Data Science in Action" MOOC on Coursera
• Having read the book "Process Mining: Data Science in Action" by Wil van der Aalst.