Connecting databases with process mining: a meta model and toolset

González López de Murillas, E., Reijers, H. A., & van der Aalst, W. M. P. (2019). Connecting databases with process mining: a meta model and toolset. Software and Systems Modeling, 18(2), 1209-1247. https://doi.org/10.1007/s10270-018-0664-7 Abstract Process mining techniques require event logs which, in many cases, are obtained from databases. Obtaining these event logs is not a Read More …

Working on Process Mining? Consider becoming a member of the IEEE Task Force on Process Mining!

If you did not join the IEEE Task Force on Process Mining yet, please consider doing so!                 >> register via https://www.tf-pm.org/subscription/form  << The IEEE Task Force on Process Mining (TFPM) was established in October 2009 as part of the IEEE Computational Intelligence Society. The set of activities and members has expanded over the last Read More …

A tour in process mining: from practice to algorithmic challenges

van der Aalst, W., Carmona, J., Chatain, T., & van Dongen, B. (2019). A tour in process mining: from practice to algorithmic challenges. In M. Koutny, L. Pomello, & L. M. Kristensen (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIV (pp. 1-35). (Lecture Notes in Computer Science (including subseries Lecture Notes in Read More …

Guided interaction exploration and performance analysis in artifact-centric process models

van Eck, M. L., Sidorova, N., & van der Aalst, W. M. P. (2019). Guided interaction exploration and performance analysis in artifact-centric process models. Business and Information Systems Engineering, 61(6), 649-663. https://doi.org/10.1007/s12599-018-0546-0 Abstract Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the Read More …

Case notion discovery and recommendation: automated event log building on databases

de Murillas, E. G. L., Reijers, H. A., & van der Aalst, W. M. P. (Accepted/In press). Case notion discovery and recommendation: automated event log building on databases. Knowledge and Information Systems. https://doi.org/10.1007/s10115-019-01430-6 Abstract Process mining techniques use event logs as input. When analyzing complex databases, these event logs can be built in many ways. Read More …

Evaluating conformance measures in process mining using conformance propositions

Syring, A. F., Tax, N., & van der Aalst, W. M. P. (2019). Evaluating conformance measures in process mining using conformance propositions. In M. Koutny, L. Pomello, & L. M. Kristensen (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIV (pp. 192-221). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Read More …

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 …

What if process predictions are not followed by good recommendations?

Dees, M., de Leoni, M., van der Aalst, W. M. P., & Reijers, H. A. (2019). What if process predictions are not followed by good recommendations? In J. vom Brocke , J. Mendling, & M. Rosemann (Eds.), 17th International Conference on Business Process Management 2019 Industry Forum: Proceedings of the Industry Forum at BPM 2019 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 …

Object-centric behavioral constraint models: a hybrid model for behavioral and data perspectives

Li, G., De Carvalho, R. M., & van der Aalst, W. M. P. (2019). Object-centric behavioral constraint models: a hybrid model for behavioral and data perspectives. In Proceeding SAC ’19 Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing (pp. 48-56). New York: Association for Computing Machinery, Inc. DOI: 10.1145/3297280.3297287 Abstract In order to maintain Read More …

Multi-instance mining: discovering synchronisation in artifact-centric processes

van Eck, M. L., Sidorova, N., & van der Aalst, W. M. P. (2019). Multi-instance mining: discovering synchronisation in artifact-centric processes. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops – BPM 2018 International Workshops, Revised Papers (pp. 18-30). (Lecture Notes in Business Information Processing; Vol. 342). Cham: Springer. DOI: Read More …

Improving merging conditions for recomposing conformance checking

Lee, W. L. J., Munoz-Gama, J., Verbeek, H. M. W., van der Aalst, W. M. P., & Sepúlveda, M. (2019). Improving merging conditions for recomposing conformance checking. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops – BPM 2018 International Workshops, Revised Papers (pp. 31-43). (Lecture Notes in Business Information Read More …

Detecting behavioral design patterns from software execution data

Liu, C., van Dongen, B. F., Assy, N., & van der Aalst, W. M. P. (2019). Detecting behavioral design patterns from software execution data. In E. Damiani, G. Spanoudakis, & L. A. Maciaszek (Eds.), Evaluation of Novel Approaches to Software Engineering – 13th International Conference, ENASE 2018, Revised Selected Papers (pp. 137-164). (Communications in Computer Read More …

Data-driven usability test scenario creation

van Eck, M. L., Markslag, E., Sidorova, N., Brosens-Kessels, A., & van der Aalst, W. M. P. (2019). Data-driven usability test scenario creation. In M. K. Lárusdóttir, M. Winckler, K. Kuusinen, P. Palanque, & C. Bogdan (Eds.), Human-Centered Software Engineering – 7th IFIP WG 13.2 International Working Conference, HCSE 2018, Revised Selected Papers (pp. 88-108). Read More …

A model-based framework to automatically generate semi-real data for evaluating data analysis techniques

Li, G., de Carvalho, R. M., & van der Aalst, W. M. P. (2019). A model-based framework to automatically generate semi-real data for evaluating data analysis techniques. In J. Filipe, A. Brodsky, M. Smialek, & S. Hammoudi (Eds.), ICEIS 2019 – Proceedings of the 21st International Conference on Enterprise Information Systems (pp. 213-220). SCITEPRESS-Science and Read More …

A general framework to identify software components from execution data

Liu, C., van Dongen, B. F., Assy, N., & van der Aalst, W. M. P. (2019). A general framework to identify software components from execution data. In G. Spanoudakis, E. Damiani, L. Maciaszek, & L. Maciaszek (Eds.), ENASE 2019 – Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering (pp. Read More …

Software architectural model discovery from execution data

Liu, C., van Dongen, B. F., Assy, N., & van der Aalst, W. M. P. (2018). Software architectural model discovery from execution data. In ENASE 2018 – Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering (pp. 3-10) Abstract During the execution of software systems, many crashes and exceptions may Read More …

Mining local process models with constraints efficiently: applications to the analysis of smart home data

Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Mining local process models with constraints efficiently: applications to the analysis of smart home data. In Proceedings of the 14th International Conference on Intelligent Environments (IE) (pp. 56-63). [8595032] Piscataway: Institute of Electrical and Electronics Engineers. DOI: 10.1109/IE.2018.00016 Abstract Sequential pattern Read More …

On the application of sequential pattern mining primitives to process discovery: overview, outlook and opportunity identification

Hassani, M., van Zelst, S. J., & van der Aalst, W. M. P. (2019). On the application of sequential pattern mining primitives to process discovery: overview, outlook and opportunity identification. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(6), [e1315]. DOI: 10.1002/widm.1315 Abstract Sequential pattern mining (SPM) is a well-studied theme in data mining, in 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 …

Configurable event correlation for process discovery from object-centric event data

Li, Guangming, Medeiros De Carvalho, Renata & van der Aalst, Wil M.P. (2018). Configurable event correlation for process discovery from object-centric event data. Proceedings – 2018 IEEE International Conference on Web Services, ICWS 2018 – Part of the 2018 IEEE World Congress on Services (pp. 203-210). Institute of Electrical and Electronics Engineers (IEEE). Abstract Many Read More …

Software process analysis methodology-a methodology based on lessons learned in embracing legacy software

Leemans, Maikel, van der Aalst, Wil M.P., van den Brand, Mark G.J., Schiffelers, Ramon R.H. & Lensink, Leonard (2018). Software process analysis methodology-a methodology based on lessons learned in embracing legacy software. Proceedings – 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018 (pp. 665-674). Piscataway: Institute of Electrical and Electronics Engineers (IEEE). Read More …

Lifecycle-Based Process Performance Analysis

Hompes, Bart F.A. & van der Aalst, Wil M.P. (2018). Lifecycle-Based Process Performance Analysis. In Dumitru Roman, Henderik A. Proper, Robert Meersman, Hervé Panetto, Christophe Debruyne & Claudio Agostino Ardagna (Eds.), On the Move to Meaningful Internet Systems. OTM 2018 Conferences – Confederated International Conferences (pp. 336-353). (Lecture Notes in Computer Science (including subseries Lecture Read More …

Fast conformance analysis based on activity log abstraction

Dixit, P.M. & van der Aalst, W.M.P. (2018). Fast conformance analysis based on activity log abstraction. 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference, Proceedings (pp. 135-144). Piscataway. Abstract Process mining techniques focus on bridging the gap between activity logs and business process management. Process discovery is a sub-field of process mining which uses Read More …

Incremental computation of synthesis rules for free-choice Petri nets

Dixit, Prabhakar M., Verbeek, H.M.W. & van der Aalst, Wil M.P. (2018). Incremental computation of synthesis rules for free-choice Petri nets. In Peter Csaba Ölveczky & Kyungmin Bae (Eds.), Formal Aspects of Component Software – 15th International Conference, FACS 2018, Proceedings (pp. 97-117). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence Read More …

Interactive data-driven process model construction

Dixit, P. M., Verbeek, H.M.W., Buijs, J. C.A.M. & van der Aalst, W. M.P. (2018). Interactive data-driven process model construction. In Xiaoyong Du, Guoliang Li, Zhanhuai Li, Juan C. Trujillo, Tok Wang Ling, Karen C. Davis & Mong Li Lee (Eds.), Conceptual Modeling – 37th International Conference, ER 2018, Proceedings (pp. 251-265). (Lecture Notes in 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 …

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 …

Discovering high-level BPMN process models from event data

Kalenkova, Anna, Burattin, Andrea, de Leoni, Massimiliano, van der Aalst, Wil & Sperduti, Alessandro (2019). Discovering high-level BPMN process models from event data. Business Process Management Journal, 25(5), 995-1019. DOI: 10.1108/BPMJ-02-2018-0051 Abstract Purpose: The purpose of this paper is to demonstrate that process mining techniques can help to discover process models from event logs, using Read More …

Analysing structured learning behaviour in Massive Open Online Courses (MOOCs) : An approach based on process mining and clustering

Beemt, A.A.J. van den, Buijs, J.C.A.M. & Aalst, W.M.P. van der (2018). Analysing structured learning behaviour in Massive Open Online Courses (MOOCs) : An approach based on process mining and clustering. International Review of Research in Open and Distance Learning, 19(5), 38-60. Abstract The increasing use of digital systems to support learning leads to a 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.

Component interface identification and behavioral model discovery from software execution data

Liu, Cong, van Dongen, Boudewijn, Assy, Nour & van der Aalst, Wil M.P. (2018). Component interface identification and behavioral model discovery from software execution data. Proceedings – 2018 ACM/IEEE 26th International Conference on Program Comprehension, ICPC 2018 (pp. 97-107). New York: Association for Computing Machinery, Inc Abstract Restructuring an object-oriented software system into a component-based Read More …