DeLiBiDa

Desire Lines in Big Data

Description

The goal of process mining is to extract process-related information from event logs, e.g., to automatically discover a process model by observing events recorded by some information system. Despite recent advances in process mining there are still important challenges that need to be addressed. In particular with respect to handling large-scale event logs. DeLiBiDa aims to develop new techniques to deal with massive event data. There are various settings where it is impossible to store events over an extended period. Therefore, we want to develop techniques for storing large event logs efficiently, for example in databases. Furthermore, we aim to develop in-database (pre)processing techniques to facilitate existing as well as new to be developed process mining technology. Finally, we plan to develop query techniques to make event-data quickly accessible for processing.

Links

Publications

  • Repairing outlier behaviour in event logs - Fani Sani, M., van Zelst, S. J., & van der Aalst, W. M. P. (2018). Repairing outlier behaviour in event logs. In W. Abramowicz, & A. Paschke (Eds.), Business Information Systems – 21st International Conference, BIS 2018, Proceedings (pp. 115-131). (Lecture Notes in Business Information Processing; Vol. 320). Cham: Springer. https://doi.org/10.1007/978-3-319-93931-5_9 Abstract One of the Read More ...
  • Computing alignments of event data and process models - van Zelst, S. J., Bolt, A., & van Dongen, B. F. (2018). Computing alignments of event data and process models. In M. Koutny, L. M. Kristensen, & W. Penczek (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIII (pp. 1-26). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Read More ...
  • Process mining with streaming data - van Zelst, S. J. (2019). Process mining with streaming data Eindhoven: Technische Universiteit Eindhoven
  • Improving alignment computation using model-based preprocessing - Syamsiyah, A., & van Dongen, B. F. (2019). Improving alignment computation using model-based preprocessing. In Proceedings – 2019 International Conference on Process Mining, ICPM 2019 (pp. 73-80). [8786043] Piscataway: Institute of Electrical and Electronics Engineers. DOI: 10.1109/ICPM.2019.00021 Abstract Alignments are a fundamental approach in conformance checking to provide an explicit relation between traces of events Read More ...
  • Online conformance checking: relating event streams to process models using prefix-alignments - van Zelst, S. J., Bolt Irondio, A. J., Hassani, M., van Dongen, B. F., & van der Aalst, W. M. P. (2019). Online conformance checking: relating event streams to process models using prefix-alignments. International Journal of Data Science and Analytics, 8(3), 269-284. DOI: 10.1007/s41060-017-0078-6 Abstract Companies often specify the intended behaviour of their business processes Read More ...
  • 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 ...
  • Native directly follows operator - Syamsiyah, A., Dongen, B. F. van, & Dijkman, R. M. (2018). Native directly follows operator. arXiv. Abstract Typical legacy information systems store data in relational databases. Process mining is a research discipline that analyzes this data to obtain insights into processes. Many different process mining techniques can be applied to data. In current techniques, an Read More ...
  • Online conformance checking using behavioural patterns - Burattin, Andrea, van Zelst, Sebastiaan J., Armas-Cervantes, Abel, van Dongen, Boudewijn F. & Carmona, Josep (2018). Online conformance checking using behavioural patterns. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management – 16th International Conference, BPM 2018, Proceedings (pp. 250-267). (Lecture Notes in Computer Science (including subseries Lecture Notes Read More ...
  • Maximizing synchronization for aligning observed and modelled behaviour - Bloemen, Vincent, van Zelst, Sebastiaan J., van der Aalst, Wil M.P., van Dongen, Boudewijn F. & van de Pol, Jaco (2018). Maximizing synchronization for aligning observed and modelled behaviour. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management – 16th International Conference, BPM 2018, Proceedings (pp. 233-249). (Lecture Notes Read More ...
  • RapidProM : mine your processes and not just your data - van der Aalst, W.M.P., Bolt Iriondo, A.J. & van Zelst, S.J. (2018). RapidProM : mine your processes and not just your data. In R. Klinkenberg & M. Hofmann (Eds.), RapidMiner : Data Mining Use Cases and Business Analytics Applications Chapman & Hall/CRC Press.

Staff

  • Boudewijn van Dongen - Boudewijn’s research focusses on conformance checking. Conformance checking is considered to be anything where observed behavior, needs to be related to already modeled behavior. Conformance checking is embedded in the larger contexts of Business Process Management and Process Mining. Boudewijn aims to develop techniques and tools to analyze databases and logs of large-scale information systems Read More ...

Former staff

  • Alifah Syamsiyah - Position: PhD Student Room: MF 7.108 Tel (internal): 2767 Links: Courses Presentations Projects Publications External links: Google scholar page Scopus page DBLP page TU/e page Recent courses Recent presentations Recent projects Recent publications
  • Wil van der Aalst - Prof.dr.ir. Wil van der Aalst is a full professor of the Process and Data Science (PADS) group at the RWTH in Aachen (Germany) and a part-time professor in the PA group. His personal research interests include process mining, business process management, workflow management, Petri nets, process modeling, and process analysis. Position: HGL Room: MF 7.064 Read More ...
  • Long Cheng - Position: PD Room: MF 7.109 Tel (internal): 3635 Links: Personal home page DBLP page TU/e employee page Projects Presentations
  • Sebastiaan (Bas) van Zelst - Bas is a PhD student within the PA group where his main research is in the area of process mining. More concretely, his research interests focus on analysing event streams without storing (too much) data. Position: PhD Student Room: MF 7.108 Tel (internal): 8687 Links: Personal home page Google scholar page Scopus page ORCID page Read More ...

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