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 …

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 …

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 …

Conformance checking: relating processes and models, relating processes and models

Carmona, J., van Dongen, B., Solti, A., & Weidlich, M. (2018). Conformance checking: relating processes and models, relating processes and models. Cham: Springer International Publishing Switzerland. https://doi.org/10.1007/978-3-319-99414-7 Abstract This book introduces readers to the field of conformance checking as a whole and outlines the fundamental relation between modelled and recorded behaviour. Conformance checking interrelates the Read More …

Overview of efficient clustering methods for high-dimensional big data streams

Hassani, M. (2019). Overview of efficient clustering methods for high-dimensional big data streams. In O. Nasraoui, & C-E. Ben N’Cir (Eds.), Clustering Methods for Big Data Analytics (pp. 25-42). (Unsupervised and Semi-Supervised Learning). Cham: Springer. https://doi.org/10.1007/978-3-319-97864-2_2 Abstract The majority of clustering approaches focused on static data. However, a big variety of recent applications and research Read More …

Using process analytics to improve healthcare processes

Hompes, B., Dixit, P., & Buijs, J. (2019). Using process analytics to improve healthcare processes. In S. Consoli, D. Reforgiato Recupero, & M. Petković (Eds.), Data Science for Healthcare: Methodologies and Applications (pp. 305-325). Cham: Springer. https://doi.org/10.1007/978-3-030-05249-2_12 Abstract Healthcare processes are inherently complex as each patient is unique and medical staff deviate from protocols, often 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 …

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 …

Visual analysis of parallel interval events

Qi, J., Liu, C., Cappers, B. C. M., & van de Wetering, H. M. M. (2018). Visual analysis of parallel interval events. In J. Johansson, F. Sadio, & T. Schreck (Eds.), 20th EG/VGTC Conference on Visualization (pp. 1-6). Geneve: The Eurographics Association. DOI: 10.2312/eurovisshort.20181074 Abstract System logs typically contain lines with time stamps that each 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 …

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 …

Process mining meets GDPR compliance: the right to be forgotten as a use case

Zaman, R., & Hassani, M. (2019). Process mining meets GDPR compliance: the right to be forgotten as a use case. In B. van Dongen, & J. Claes (Eds.), ICPM Doctoral Consortium 2019: Proceedings of the ICPM 2019 Doctoral Consortium co-located with 1st International Conference on Process Mining (ICPM 2019) (CEUR Workshop Proceedings; Vol. 2432). CEUR-WS.org. 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 …

Optimizing customer journey using process mining and sequence-aware recommendation

Terragni, A., & Hassani, M. (2019). Optimizing customer journey using process mining and sequence-aware recommendation. In SAC ’19 Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing (pp. 57-65). New York: Association for Computing Machinery, Inc. DOI: 10.1145/3297280.3297288 Abstract Customer journey analysis aims at understanding customer behavior both in the traditional offline setting and through Read More …

Online comparison of streaming process discovery algorithms

Baskar, K., & Hassani, M. (2019). Online comparison of streaming process discovery algorithms. In B. Depaire, J. De Smedt , & M. Dumas (Eds.), Proceedings of the Dissertation Award, Doctoral Consortium, and Demonstration Track at BPM 2019 co-located with 17th International Conference on Business Process Management (BPM 2019) (pp. 164-168). (CEUR Workshop Proceedings; Vol. 2420). 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 …

Mining local process models and their correlations

Genga, L., Tax, N., & Zannone, N. (2019). Mining local process models and their correlations. In M. van Keulen, P. Ceravolo, & K. Stoffel (Eds.), Data-Driven Process Discovery and Analysis – 7th IFIP WG 2.6 International Symposium, SIMPDA 2017, Revised Selected Papers (pp. 65-88). (Lecture Notes in Business Information Processing; Vol. 340). Cham: Springer. DOI: Read More …

Learning process models in IoT Edge

Cheng, L., Liu, C., Liu, Q., Duan, Y., & Murphy, J. (2019). Learning process models in IoT Edge. In C. K. Chang, P. Chen, M. Goul, K. Oyama, S. Reiff-Marganiec, Y. Sun, S. Wang, … Z. Wang (Eds.), Proceedings – 2019 IEEE World Congress on Services, SERVICES 2019 (pp. 147-150). [8817302] Piscataway: Institute of Electrical 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 …

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 …

Ensemble-based prediction of business processes bottlenecks with recurrent concept drifts

Spenrath, Y., & Hassani, M. (2019). Ensemble-based prediction of business processes bottlenecks with recurrent concept drifts. In P. Papotti (Ed.), Proceedings of the Workshops of the EDBT/ICDT 2019 Joint Conference: Lisbon, Portugal, March 26, 2019 (CEUR Workshop Proceedings; Vol. 2322). CEUR-WS.org. Abstract Bottleneck prediction is an important sub-task of process mining that aims at optimizing Read More …

Efficiently computing alignments: algorithm and datastructures

van Dongen, B. F. (2019). Efficiently computing alignments: algorithm and datastructures. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops – BPM 2018 International Workshops, Revised Papers (pp. 44-55). (Lecture Notes in Business Information Processing; Vol. 342). Springer. DOI: 10.1007/978-3-030-11641-5_4 Abstract Conformance checking is considered to be anything where observed 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 …

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 …

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 …

Concept drift detection of event streams using an adaptive window

Hassani, M. (2019). Concept drift detection of event streams using an adaptive window. In 33rd International ECMS Conference on Modelling and Simulation, ECMS 2019 (pp. 230-239). [DSM 73] (Proceedings – European Council for Modelling and Simulation, ECMS; Vol. 33). Abstract Process mining is an emerging data mining task of gathering valuable knowledge out of the Read More …

Business process improvement activities: differences in organizational size, culture, and resources

Beerepoot, I., van de Weerd, I., & Reijers, H. A. (2019). Business process improvement activities: differences in organizational size, culture, and resources. In T. Hildebrandt, B. F. van Dongen, M. Röglinger, & J. Mendling (Eds.), Business Process Management – 17th International Conference, BPM 2019, Proceedings (pp. 402-418). (Lecture Notes in Computer Science (including subseries Lecture Read More …

An effective and efficient approach for supporting the generation of synthetic memory reference traces via hierarchical hidden/non-hidden Markov Models

Cuzzocrea, A., Mumolo, E., & Hassani, M. (2019). An effective and efficient approach for supporting the generation of synthetic memory reference traces via hierarchical hidden/non-hidden Markov Models. In Proceedings – 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 (pp. 2953-2959). [8616498] Institute of Electrical and Electronics Engineers. DOI: 10.1109/SMC.2018.00502 Abstract This paper Read More …

An approach for workflow improvement based on outcome and time remaining prediction

Galdo Seara, L., & De Carvalho, R. M. (2019). An approach for workflow improvement based on outcome and time remaining prediction. In S. Hammoudi, B. Selic, & L. F. Pires (Eds.), MODELSWARD 2019 – Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development (pp. 475-482). Setúbal: SCITEPRESS-Science and Technology Publications, Lda.. DOI: Read More …