Martin, N., Pufahl, L., & Mannhardt, F. (2021). Detection of batch activities from event logs. Information Systems, 95, [101642]. https://doi.org/10.1016/j.is.2020.101642 Abstract Organizations carry out a variety of business processes in order to serve their clients. Usually supported by information technology and systems, process execution data is logged in an event log. Process mining uses this Read More …
On January 15th, Dominique Sommers started working as PhD student in the PA group. Dominique will work under the supervision of Boudewijn van Dongen. A big welcome to Dominique!
Data als brandstof voor kunstmatige intelligentie; TU/e start nieuwe masteropleiding EINDHOVEN – Zonder brandstof komt een auto niet vooruit. Hetzelfde principe gaat op voor kunstmatige intelligentie: zonder voldoende en goede data is daar niets intelligents aan. Een nieuwe master van de TU/e combineert daarom die twee disciplines. Bron: ED
Summary In the context of the “Process Mining in Logistics” research project between Vanderlande Industries and TU Eindhoven, we are offering multiple Master projects on process mining on event data of large-scale material handling systems. The fundamental challenges addressed are size and volume (logistics process data is significantly larger than business processes) and integration of Read More …
Summary In the context of the “Process Mining in Logistics” research project between Vanderlande Industries, we are offering multiple Master projects on process mining on event data of large-scale material handling systems. The fundamental challenges addressed are size (logistics processes are a factor 10-100 larger than business processes), reliable performance analysis and process prediction. We Read More …
Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based Read More …
Understanding and predicting behavior of people and machines in a shared setting (task, project, factory, process, organization) is central to Data Science and Artificial Intelligence. Actions of people and machines can be recorded as discrete events in event sequences (logs), event databases (tables, graphs), and real-time event streams. Learning behavioral models of discrete event data Read More …
Only for BDMA students. Links Osiris Staff
Learning goals Students gain insight in basic techniques for processing large amounts of data in an efficient, reliable, and consistent way. Students develop skills in understanding, interpreting, and documenting data and information in the context of realistic scenarios. Students get understanding of the data life cycle and develop skills for structuring their solutions of practical Read More …
In this meeting the student gets insight into the study program. Staff
In this meeting the student gets insight into the study program. Staff
In this seminar, a group of master students will get in touch with research in the area of Information Systems, where Process Mining and Process Analysis from Event Data are the central themes. We study recent publications in the area of process mining and practical applications on real-life examples, to provide a good insight into Read More …
People interested in the ‘process side’ of information systems can take the course ‘Capita selecta architecture of information systems’. This course will be organized in an ad-hoc manner taking into account the interests of the student. The focus will always be on a particular ‘hot topic’ in the information systems domain. The course can, in Read More …
In this DBL, students get a chance to get a first glimpse on process mining. Through a practical case, students will learn the basics of data mining in the context of (business) processes and they build a prediction model for process aspects. In the basic course Data Analytics for Engineers, students have seen the basics Read More …
The objective of the Data Challenge courses is to teach students how to perform large-scale data-driven analyses themselves, combining the technical skills acquired earlier in the Data Science program with insights gained in methodological courses. In the first Data Challenge 1, students will get the possibility to apply the methods and techniques acquired during the Read More …
The objective of the Data Challenge courses is to teach students how to perform large-scale data-driven analyses themselves, combining technical skills acquired earlier with insights gained in methodological courses. The focus of Data Challenge 3 is to take students through the entire life-cycle of a data analysis for public stakeholders, starting in a typical situation Read More …
The Real-Time Process Mining course is an advanced master-level process mining course where the following main contents will be covered: Dimensionality reduction and efficient preprocessing of log files Stream data mining Advanced topics in process mining, like: stream process discovery, online conformance checking and concept drift detection When the focus shifts to advanced topics in Read More …
