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 …

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 …

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 …

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.

A native operator for process discovery

Syamsiyah, Alifah, van Dongen, Boudewijn F. & Dijkman, Remco M. (2018). A native operator for process discovery. In Hui Ma, Günther Pernul, Abdelkader Hameurlain, Sven Hartmann & Roland R. Wagner (Eds.), Database and Expert Systems Applications – 29th International Conference, DEXA 2018, Proceedings (pp. 292-300). (Lecture Notes in Computer Science (including subseries Lecture Notes in Read More …

Repairing outlier behaviour in event logs

Fani Sani, Mohammadreza, van Zelst, Sebastiaan J. & van der Aalst, Wil 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, No. 320). Cham: Springer. Abstract One of the main challenges Read More …

Filtering spurious events from event streams of business processes

van Zelst, Sebastiaan J., Fani Sani, Mohammadreza, Ostovar, Alireza, Conforti, Raffaele & La Rosa, Marcello (2018). Filtering spurious events from event streams of business processes. Advanced Information Systems Engineering – 30th International Conference, CAiSE 2018, Proceedings (pp. 35-52). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Read More …

An experimental evaluation of the generalizing capabilities of process discovery techniques and black-box sequence models

Tax, N., van Zelst, S.J. & Teinemaa, I. (2018). An experimental evaluation of the generalizing capabilities of process discovery techniques and black-box sequence models. In Palash Bera, Jens Gulden, Iris Reinhartz-Berger, Wided Guédria, Sérgio Guerreiro & Rainer Schmidt (Eds.), Enterprise, Business-Process and Information Systems Modeling (pp. 165-180). (Lecture Notes in Business Information Processing). Dordrecht: Springer Read More …

DB-XES : Enabling process discovery in the large

Syamsiyah, Alifah, Van Dongen, Boudewijn F. & van der Aalst, Wil M.P. (2018). DB-XES : Enabling process discovery in the large. Data-Driven Process Discovery and Analysis – 6th IFIP WG 2.6 International Symposium, SIMPDA 2016, Revised Selected Papers (pp. 53-77). (Lecture Notes in Business Information Processing, No. 307). BHRA / Springer Verlag. Abstract Dealing with Read More …

Recurrent process mining with live event data

Syamsiyah, Alifah, van Dongen, Boudewijn F. & van der Aalst, Wil M.P. (2018). Recurrent process mining with live event data. Business Process Management Workshops – BPM 2017 International Workshops, Revised Papers (pp. 178-190). (Lecture Notes in Business Information Processing, No. 308). BHRA / Springer Verlag. Abstract In organizations, process mining activities are typically performed in Read More …

Improving process discovery results by filtering outliers using conditional behavioural probabilities

Sani, Mohammadreza Fani, van Zelst, Sebastiaan J. & van der Aalst, Wil M.P. (2018). Improving process discovery results by filtering outliers using conditional behavioural probabilities. Business Process Management Workshops – BPM 2017 International Workshops, Revised Papers (pp. 216-229). (Lecture Notes in Business Information Processing, No. 308). Berlin: Springer. Abstract Process discovery, one of the key Read More …

Event stream-based process discovery using abstract representations

van Zelst, S.J., van Dongen, B.F. & van der Aalst, W.M.P. (2018). Event stream-based process discovery using abstract representations. Knowledge and Information Systems, 54(2), 407-435. Abstract The aim of process discovery, originating from the area of process mining, is to discover a process model based on business process execution data. A majority of process discovery Read More …

Discovering workflow nets using integer linear programming

van Zelst, S.J., van Dongen, B.F., van der Aalst, W.M.P. && Verbeek, H.M.W. (2018). Discovering workflow nets using integer linear programming. Computing, 100(5), 529-556. Abstract Process mining is concerned with the analysis, understanding and improvement of business processes. Process discovery, i.e. discovering a process model based on an event log, is considered the most challenging Read More …

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 Read More …

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 …

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 …