Process mining for six sigma: a guideline and tool support

Graafmans, T. L. F., Türetken, O., Poppelaars, J. J. G. H., & Fahland, D. (Accepted/In press). Process mining for six sigma: a guideline and tool support. Business & Information Systems Engineering. Abstract Process mining offers a set of techniques for gaining data-based insights into business processes from event logs. The literature acknowledges the potential benefits Read More …

Storing and querying multi-dimensional process event logs using graph databases

Esser, S., & Fahland, D. (2019). Storing and querying multi-dimensional process event logs using graph databases. In 15th International Workshop on Business Process Intelligence Abstract Process event data is usually stored either in a sequential process event log or in a relational database. While the sequential, single-dimensional nature of event logs aids querying for event Read More …

Predictive performance monitoring of material handling systems using the performance spectrum

Denisov, V., Fahland, D., & van der Aalst, W. M. P. (2019). Predictive performance monitoring of material handling systems using the performance spectrum. In Proceedings – 2019 International Conference on Process Mining, ICPM 2019 (pp. 137-144). [8786068] Piscataway: Institute of Electrical and Electronics Engineers. DOI: 10.1109/ICPM.2019.00029 Abstract Predictive performance analysis is crucial for supporting operational Read More …

Performance mining for batch processing using the performance spectrum

Klijn, E. L., & Fahland, D. (2019). Performance mining for batch processing using the performance spectrum. In 15th International Workshop on Business Process Intelligence Abstract Performance analysis from process event logs is a central element of business process management and improvement. Established performance analysis techniques aggregate time-stamped event data to identify bottlenecks or to visualize Read More …

Describing behavior of processes with many-to-many interactions

Fahland, D. (2019). Describing behavior of processes with many-to-many interactions. In S. Haar, & S. Donatelli (Eds.), Application and Theory of Petri Nets and Concurrency – 40th International Conference, PETRI NETS 2019, Proceedings (pp. 3-24). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11522 LNCS). Read More …

Information-preserving abstractions of event data in process mining

Leemans, S. J. J., & Fahland, D. (2019). Information-preserving abstractions of event data in process mining. Knowledge and Information Systems. DOI: 10.1007/s10115-019-01376-9 Abstract Process mining aims at obtaining information about processes by analysing their past executions in event logs, event streams, or databases. Discovering a process model from a finite amount of event data thereby Read More …

The performance spectrum miner : visual analytics for fine-grained performance analysis of processes

Denisov, Vadim, Belkina, Elena, Fahland, Dirk & van der Aalst, Wil M.P. (2018). The performance spectrum miner : visual analytics for fine-grained performance analysis of processes. CEUR Workshop Proceedings, 2196, 96-100. Abstract We present the Performance Spectrum Miner, a ProM plugin, which implements a new technique for fine-grained performance analysis of processes. The technique uses Read More …

Who is behind the model? classifying modelers based on pragmatic model features

Burattin, Andrea, Soffer, Pnina, Fahland, Dirk, Mendling, Jan, Reijers, Hajo A., Vanderfeesten, Irene, Weidlich, Matthias & Weber, Barbara (2018). Who is behind the model? classifying modelers based on pragmatic model features. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management – 16th International Conference, BPM 2018, Proceedings (pp. 322-338). Read More …

Unbiased, fine-grained description of processes performance from event data

Denisov, V.V., Fahland, D. & van der Aalst, W.M.P. (2018). Unbiased, fine-grained description of processes performance from event data. Business Process Management – 16th International Conference, BPM 2018, Sydney, NSW, Australia, September 9-14, 2018, Proceedings. (pp. 139-157). (Lecture Notes in Computer Science, No. 11080). Springer. Abstract Performance is central to processes management and event data Read More …

Scalable process discovery and conformance checking

Leemans, S.J.J., Fahland, D. & van der Aalst, W.M.P. (2018). Scalable process discovery and conformance checking. Software and Systems Modeling, 17(2), 599-631. Abstract Considerable amounts of data, including process events, are collected and stored by organisations nowadays. Discovering a process model from such event data and verification of the quality of discovered models are important Read More …

Using behavioral context in process mining : exploration, preprocessing and analysis of event data

Lu, X. (2018). Using behavioral context in process mining : exploration, preprocessing and analysis of event data. Eindhoven: Technische Universiteit Eindhoven. ((Co-)promot.: Wil van der Aalst, Dirk Fahland & Nicola Zannone)

A visualization of human physical risks in manufacturing processes using BPMN

Polderdijk, Melanie, Vanderfeesten, Irene, Erasmus, Jonnro, Traganos, Kostas, Bosch, Tim, van Rhijn, Gu & Fahland, Dirk (2018). A visualization of human physical risks in manufacturing processes using BPMN. Business Process Management Workshops – BPM 2017 International Workshops, Revised Papers (pp. 732-743). (Lecture Notes in Business Information Processing, No. 308). Springer. Abstract Process models are schematic Read More …

The imprecisions of precision measures in process mining

Tax, N., Lu, X., Sidorova, N., Fahland, D. & van der Aalst, W.M.P. (2018). The imprecisions of precision measures in process mining. Information Processing Letters, 135, 1-8. Abstract In process mining, precision measures are used to quantify how much a process model overapproximates the behavior seen in an event log. Although several measures have been Read More …

Dynamic skipping and blocking, dead path elimination for cyclic workflows, and a local semantics for inclusive gateways

Fahland, Dirk & Völzer, Hagen (2018). Dynamic skipping and blocking, dead path elimination for cyclic workflows, and a local semantics for inclusive gateways. Information Systems, 78, 126-143. Abstract We propose and study dynamic versions of the classical flexibility constructs ‘skip’ and ‘block’ for workflows and motivate and define a formal semantics for them. We show Read More …

Linking data and process perspectives for conformance analysis

Alizadeh, M., Lu, X., Fahland, D., Zannone, N. & van der Aalst, W.M.P. (2018). Linking data and process perspectives for conformance analysis. Computers and Security, 73, 172-193. Abstract The detection of data breaches has become a major challenge for most organizations. The problem lies in the fact that organizations often lack proper mechanisms to control Read More …

Publications in 2017

Article Scientific peer reviewed Arriagada-Benítez, M., Sepúlveda, M., Munoz-Gama, J. & Buijs, J.C.A.M. (2017). Strategies to automatically derive a process model from a configurable process model based on event data. Applied Sciences, 7(10):1023. Bolt, A., de Leoni, M. & van der Aalst, W.M.P. (2017). Process variant comparison: using event logs to detect differences in behavior Read More …

Publications in 2016

Article Scientific peer reviewed Van Der Aa, Han, Leopold, H. & Reijers, H.A. (2016). Dealing with behavioral ambiguity in textual process descriptions. Lecture notes in computer science, 9850, 271-288. Scopus. van der Aa, J.H., Reijers, H.A. & Vanderfeesten, I.T.P. (2016). Designing like a pro : the automated composition of workflow activities. Computers in Industry, 75, Read More …

Publications in 2015

Article Scientific peer reviewed Adriansyah, Arya, Munoz Gama, Jorge, Carmona, J., van Dongen, Boudewijn & van der Aalst, Wil (2015). Measuring precision of modeled behavior. Information Systems and e-Business Management, 13(1), 37-67. Claes, Jan, Vanderfeesten, Irene, Pinggera, J., Reijers, Hajo, Weber, B. & Poels, G. (2015). A visual analysis of the process of process modeling. Read More …