Organizations are constantly trying to improve the way their businesses perform. To this end, managers have to take decisions on changes to the operational processes. However, for decision making, it is of the utmost importance to have a thorough understanding of the operational processes as they take place in the organization.

Typically, such operational processes are supported by information systems that record events as they take place in real life in so-called event logs. Process Mining techniques allow for extracting information from event logs. For example, the audit trails of a workflow management system or the transaction logs of an enterprise resource planning system can be used to discover models describing processes, organizations, and products. Moreover, it is possible to use process mining to monitor deviations (e.g., comparing the observed events with predefined models or business rules in the context of SOX).

Process mining is closely related to BAM (Business Activity Monitoring), BOM (Business Operations Management), BPI (Business Process Intelligence), and data/workflow mining. Unlike classical data mining techniques the focus is on processes and questions that transcend the simple performance-related queries supported by tools such as Business Objects, Cognos BI, and Hyperion.

In this seminar, students are introduced to the research being conducted in the Architecture of Information Systems group of this university. Specifically, this seminar focuses on the state-of-the-art research on Process Mining. To emphasize that Process Mining is not only a research area, but has gained increasing interest from Industry, practical application will be considered.

In this seminar, a group of master students will get in touch with research in the area of Information Systems, where Process Mining provides the central theme.

By combining recent publications in the area of process mining with practical applications on real-life examples, this course provides a good insight into the research of the AIS group at Eindhoven University of Technology.

The research area will be studied in the following ways:

• Lectures by staff members and guest lectures from industry (depends on the number of students)
• Research papers and/or book chapters will be studied and presented by students, with a focus on research questions.
• Examples related to the presented material will be elaborated.
• If suitable, experiments related to these examples will be executed, either by using existing implementations such as ProM and/or Magnaview, or by developing ad-hoc implementations.

It is advised (not compulsory) for students to have some background in Business Process Modelling, Process Mining, Data Mining and/or Visualization, for example through the following courses:

• 2II05 - Business Information Systems
• 1BB30 - Business Process Modelling
• 2II55 - Business Information Systems
• 1BM45 - Process Mining
• 2II15 - Data Mining and Knowledge Systems
• 2IV35 - Visualization

The lectures will be given in English, twice a week, in a two hour block. The lectures will be a mixture of discussions sessions centered around scientific articles and invited lectures (if there are enough students), where real-life case studies are presented by people from industry (MagnaView, Fluxicon, FuturaTech, AMC Hospital, …). Attendance is compulsory, unless good reasons can be given not to attend.

(to be determined)

No instructions are scheduled for the course.

Download all papers as ZIP file(25 MB)

• Process Diagnostics: a Method Based on Process Mining
  M. Bozkaya, J.M.A.M. Gabriels, and J.M.E.M. van der Werf
  To appear in the proceedings of International Conference on Information, Process, and Knowledge Management (eKNOW) 2009
  Download page

Control Flow Analysis Plugins Documentation

• Process Mining: A Two-Step Approach to Balance Between Underfitting and Overfitting
  W.M.P. van der Aalst, V. Rubin, H.M.W. Verbeek, B.F. van Dongen, E. Kindler, and C.W. Günther
  To appear in Software and Systems Modeling (SoSyM)
  Download page

• Genetic Process Mining
  W.M.P. van der Aalst, A.K. Alves de Medeiros and A.J.M.M. Weijters
  26th International Conference on Applications and Theory of Petri Nets (ICATPN 2005), G. Ciardo and P. Darondeau, LNCS 3536, pages 48-69, 2005
  © Springer-Verlag Berling Heidelberg 2005
  Download page

• Fuzzy Mining: Adaptive Process Simplification Based on Multi-perspective Metrics
  C.W. Günther and W.M.P. van der Aalst
  In G. Alonso, P. Dadam, and M. Rosemann, editors, International Conference on Business Process Management (BPM 2007), volume 4714 of Lecture Notes in Computer Science, pages 328-343. Springer-Verlag, Berlin, 2007
  Download page

• Rediscovering Workflow Models from Event-Based Data using Little Thumb
  A.J.M.M. Weijters and W.M.P. van der Aalst
  Integral Computer-Aided Engineering, 10(2):151-162, 2003
  Download page

• Process Mining with the HeuristicsMiner Algorithm
  A.J.M.M. Weijters, W.M.P. van der Aalst and A.K. Alves de Medeiros
  Beta Research paper 166, 2006
  Download page

• Understanding Spaghetti Models with Sequence Clustering for ProM
  G.M. Veiga and D.R. Ferreira
  International Workshop on Business Process Intelligence, 2009
  Download page

Performance Analysis Plugins Documentation

• Performance Analysis of Business Processes Through Process Mining
  Peter Hornix
  Master's Thesis. Technische Universiteit Eindhoven, Eindhoven, The Netherlands, 2007.
  Download page

• Process Mining: Fuzzy Clustering and Performance Visualization
  B.F. van Dongen and A. Adriansyah
  5th Workshop on Business Process Intelligence (BPI 09), 2009.
  Download page

• Supporting Process Mining by Showing Events at a Glance
  M. Song and W.M.P. van der Aalst
  In K. Chari, A. Kumar editors, Seventeenth Annual Workshop on Information Technologies and Systems (WITS'07), pp.139–145, Montreal, Canada, December 8-9, 2007
  Download page

Organizational Analysis Plugins Documentation

• Discovering Social Networks from Event Logs
  W.M.P. van der Aalst and H.A. Reijers and M. Song
  Computer Supported Cooperative Work, volume 14, number 6, pages 549-593, 2005
  Download page

• Towards Comprehensive Support for Organizational Mining
  M. Song and W.M.P. van der Aalst
  Decision Support Systems, Volume 46, Number 1, Pages 300-307, Dec. 2008
  Download page

• Process Mining Applied to the Test Process of Wafer Steppers in ASML
  A. Rozinat, I.S.M. de Jong, C.W. Günther, and W.M.P. van der Aalst
  IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews, Vol. 39, No. 4, Pages 474–479, 2009
  Download page

• Application of Process Mining in Healthcare – A Case Study in a Dutch Hospital
  R.S. Mans, M.H. Schonenberg, M. Song, W.M.P. van der Aalst and P.J.M. Bakker
  A. Fred, J. Filipe, and H. Gamboa (Eds.): BIOSTEC 2008, CCIS 25, pp. 425–438, 2008
  Download page

• Extracting user profiles with Process Mining at Philips Medical Systems
  K. van Uden
  Master's Thesis. Technische Universiteit Eindhoven, Eindhoven, The Netherlands, 2008.
  Download page

ProM Homepage

The exam consists of an individual assignment, where each student has to apply the theory on real-life logs. For this purpose, we use an (anonimized) logs from Dutch municipalities.

Some of the logs will be presented with a specific question, whereas other logs are given for a more general analysis.

At the end of the course, students are expected to present their case to the other students, after which a grade is determined. During these presentations, all students are expected to be present, but also all industry-lectures will be there to assess the results.

• More on Process Mining Main Process Mining Website

• LinkedIn. Group on Process Mining LinkedIn. Group on Process Mining

• OWInfo page of the course 2II96 Seminar Architecture of Information Systems

• MagnaView Homepage Magnaview

• Futura Technology Homepage Futuratech

• Fluxicon Process Laboratories Homepage Fluxicon Process Laboratories