Selected Topics in Process Mining
Reference: PADS website
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.
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.