Extensions to the bupaR Ecosystem: An Overview

Janssenswillen, G., Mannhardt, F., Creemers, M., Depaire, B., Jans, M., Jooken, L., Martin, N., & Van Houdt, G. (2020). Extensions to the bupaR Ecosystem: An Overview. In Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020) (pp. 43-46). (CEUR Workshop Proceedings; Vol. Read More …

Framework for process discovery from sensor data

Koschmider, A., Janssen, D., & Mannhardt, F. (2020). Framework for process discovery from sensor data. CEUR Workshop Proceedings, 2628, 32-38. Abstract Process mining can give valuable insights into how real-life activities are performed when extracting meaningful activities instances from raw sensor events. However, in many cases, the event data generated during the execution of a Read More …

MINING E-MAIL CONVERSATIONS TO ENRICH EVENT LOGS: AN EXPLORATORY CASE STUDY OF A HIRING PROCESS IN A NORWEGIAN MUNICIPALITY

Goday-Verdaguer , A., Mannhardt, F., & Torvatn, H. Y. (2020). MINING E-MAIL CONVERSATIONS TO ENRICH EVENT LOGS: AN EXPLORATORY CASE STUDY OF A HIRING PROCESS IN A NORWEGIAN MUNICIPALITY. In Proceedings of the NOKOBIT conference 24-25th of November 2020 (Vol. 28) https://ojs.bibsys.no/index.php/Nokobit/article/view/867 Abstract Process improvement is an important challenge for the public sector, which struggles Read More …

Quantifying the Re-identification Risk of Event Logs for Process Mining: Empiricial Evaluation Paper

Nuñez von Voigt, S., Fahrenkrog-Petersen, S. A., Janssen, D., Koschmider, A., Tschorsch, F., Mannhardt, F., Landsiedel, O., & Weidlich, M. (2020). Quantifying the Re-identification Risk of Event Logs for Process Mining: Empiricial Evaluation Paper. In S. Dustdar, E. Yu, V. Pant, C. Salinesi, & D. Rieu (Eds.), Advanced Information Systems Engineering – 32nd International Conference, Read More …

Detailed Performance Diagnosis Based on Production Timestamps: A Case Study

de Man, J. C., & Mannhardt, F. (2019). Detailed Performance Diagnosis Based on Production Timestamps: A Case Study. In F. Ameri, K. E. Stecke, G. von Cieminski, & D. Kiritsis (Eds.), Advances in Production Management Systems. Production Management for the Factory of the Future – IFIP WG 5.7 International Conference, APMS 2019, Proceedings (pp. 708-715). Read More …

ELPaaS: Event log privacy as a service

Bauer, M., Fahrenkrog-Petersen, S. A., Koschmider, A., Mannhardt, F., van der Aa, H., & Weidlich, M. (2019). ELPaaS: Event log privacy as a service. In B. Depaire, J. de Smedt, & M. Dumas (Eds.), BPMT 2019 BPM 2019 Dissertation Award, Doctoral Consortium, and Demonstration Track: Proceedings of the Dissertation Award, Doctoral Consortium, and Demonstration Track Read More …

Estimating the impact of incidents on process delay

Mannhardt, F., Arnesen, P., & Landmark, A. D. (2019). Estimating the impact of incidents on process delay. In Proceedings – 2019 International Conference on Process Mining, ICPM 2019 (pp. 49-56). [8786065] (Proceedings – 2019 International Conference on Process Mining, ICPM 2019). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM.2019.00018 Abstract Process mining reveals how processes in Read More …

Mining railway traffic control logs

Mannhardt, F., & Landmark, A. D. (2019). Mining railway traffic control logs. Transportation Research Procedia, 37, 227-234. https://doi.org/10.1016/j.trpro.2018.12.187 Abstract Railway traffic is a set of interrelated processes that are centrally controlled. Despite optimized train schedules, train dispatchers still take ad-hoc decisions on the scheduling of trains in the context of unplanned events. Train orders are Read More …

On the Contextualization of Event-Activity Mappings

Koschmider, A., Mannhardt, F., & Heuser, T. (2019). On the Contextualization of Event-Activity Mappings. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops – BPM 2018 International Workshops, Revised Papers (pp. 445-457). (Lecture Notes in Business Information Processing; Vol. 342). Springer. https://doi.org/10.1007/978-3-030-11641-5_35 Abstract Event log files are used as input Read More …

User-centered and privacy-driven process mining system design for IoT

Michael, J., Koschmider, A., Mannhardt, F., Baracaldo, N., & Rumpe, B. (2019). User-centered and privacy-driven process mining system design for IoT. In M. Ruiz, & C. Cappiello (Eds.), Information Systems Engineering in Responsible Information Systems – CAiSE Forum 2019, Proceedings (pp. 194-206). (Lecture Notes in Business Information Processing; Vol. 350). Springer. https://doi.org/10.1007/978-3-030-21297-1_17 Abstract Process mining Read More …

A taxonomy for combining activity recognition and process discovery in industrial environments

Mannhardt, F., Bovo, R., Oliveira, M. F., & Julier, S. (2018). A taxonomy for combining activity recognition and process discovery in industrial environments. In D. Camacho, P. Novais, A. J. Tallón-Ballesteros, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2018 – 19th International Conference, Proceedings (pp. 84-93). (Lecture Notes in Computer Read More …

Privacy Challenges for Process Mining in Human-Centered Industrial Environments

Mannhardt, F., Petersen, S. A., & Oliveira, M. F. (2018). Privacy Challenges for Process Mining in Human-Centered Industrial Environments. In Proceedings – 2018 International Conference on Intelligent Environments, IE 2018 (pp. 64-71). [8595033] (Proceedings – 2018 International Conference on Intelligent Environments, IE 2018). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/IE.2018.00017 Abstract Operators in industrial manufacturing Read More …

Revealing work practices in hospitals using process mining

Mannhardt, F., & Toussaint, P. J. (2018). Revealing work practices in hospitals using process mining. In G. O. Klein, D. Karlsson, A. Moen, & A. Ugon (Eds.), Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth – Proceedings of MIE 2018 (pp. 281-285). (Studies in Health Technology and Informatics; Vol. 247). 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 …

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 …

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 …

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 …