Visualizing Token Flows Using Interactive Performance Spectra

van der Aalst, W. M. P., Tacke Genannt Unterberg, D., Denisov, V., & Fahland, D. (2020). Visualizing Token Flows Using Interactive Performance Spectra. In R. Janicki, N. Sidorova, & T. Chatain (Eds.), Application and Theory of Petri Nets and Concurrency – 41st International Conference, PETRI NETS 2020, Proceedings (pp. 369-380). (Lecture Notes in Computer Science Read More …

Repairing Event Logs with Missing Events to Support Performance Analysis of Systems with Shared Resources

Denisov, V., Fahland, D., & van der Aalst, W. M. P. (2020). Repairing Event Logs with Missing Events to Support Performance Analysis of Systems with Shared Resources. In R. Janicki, N. Sidorova, & T. Chatain (Eds.), Application and Theory of Petri Nets and Concurrency – 41st International Conference, PETRI NETS 2020, Proceedings (pp. 239-259). (Lecture Notes Read More …

Multi-dimensional performance analysis and monitoring using integrated performance spectra

Denisov, V., Fahland, D., & Van Der Aalst, W. M. P. (2020). Multi-dimensional performance analysis and monitoring using integrated performance spectra. In C. Di Ciccio (Ed.), Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020): Padua, Italy, October 4-9, 2020 (pp. 27-30). Read More …

Identifying and reducing errors in remaining time prediction due to inter-case dynamics

Klijn, E. L., & Fahland, D. (2020). Identifying and reducing errors in remaining time prediction due to inter-case dynamics. In B. van Dongen, M. Montali, & M. T. Wynn (Eds.), Proceedings – 2020 2nd International Conference on Process Mining, ICPM 2020 (pp. 25-32). [9229927] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM49681.2020.00015 Abstract Remaining time prediction Read More …

Detecting system-level behavior leading to dynamic bottlenecks

Toosinezhad, Z., Fahland, D., Köroglu, Ö., & Van Der Aalst, W. M. P. (2020). Detecting system-level behavior leading to dynamic bottlenecks. In B. van Dongen, M. Montali, & M. T. Wynn (Eds.), Proceedings – 2020 2nd International Conference on Process Mining, ICPM 2020 (pp. 17-24). [9230102] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM49681.2020.00014 Abstract Dynamic Read More …

Defining meaningful local process models

Brunings, M., Fahland, D., & van Dongen, B. (2020). Defining meaningful local process models. In W. van der Aalst, R. Bergenthum, & J. Carmona (Eds.), ATAED 2020 Algorithms & Theories for the Analysis of Event Data 2020: Proceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data 2020: Satellite event Read More …

Event abstraction for process mining using supervised learning techniques

Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Event abstraction for process mining using supervised learning techniques. In Y. Bi, S. Kapoor, & R. Bhatia (Eds.), Proceedings of the SAI Intelligent Systems Conference (IntelliSys 2016), 21-22 September 2016, London, United Kingdom (pp. 251-269). (Lecture Notes in Networks and Systems; Read More …

Data Minimisation as Privacy and Trust Instrument in Business Processes

Zaman, R., Hassani, M., & van Dongen, B. F. (Accepted/In press). Data Minimisation as Privacy and Trust Instrument in Business Processes. In Business Process Management Workshops (BPM 2020) Springer. Abstract Data is vital for almost all sorts of business processes and workflows. However, the possession of personal data of other beings bear consequences. Data is Read More …

Facilitating GDPR compliance: the H2020 BPR4GDPR approach

Lioudakis, G. V., Koukovini, M. N., Papagiannakopoulou, E. I., Dellas, N., Kalaboukas, K., de Carvalho, R. M., Hassani, M., Bracciale, L., Bianchi, G., Juan-Verdejo, A., Alexakis, S., Gaudino, F., Cascone, D., & Barracano, P. (2020). Facilitating GDPR compliance: the H2020 BPR4GDPR approach. In I. O. Pappas, I. O. Pappas, P. Mikalef, L. Jaccheri, J. Krogstie, Read More …

Predicting Business Process Bottlenecks In Online Events Streams Under Concept Drifts

Spenrath, Y., & Hassani, M. (2020). Predicting Business Process Bottlenecks In Online Events Streams Under Concept Drifts. In M. Steglich, C. Muller, G. Neumann, & M. Walther (Eds.), Proceedings of European Council for Modelling and Simulation (ECMS) 2020 (pp. 190-196). (Proceedings European Council for Modelling and Simulation; Vol. 34, No. 1). European Council for Modeling Read More …

Why did my Consumer Shop? Learning an Efficient Distance Metric for Retailer Transaction Data

Spenrath, Y., Hassani, M., van Dongen, B. F., & Tariq, H. (Accepted/In press). Why did my Consumer Shop? Learning an Efficient Distance Metric for Retailer Transaction Data. In Proceedings of ECML PKDD 2020 Abstract Transaction analysis is an important part in studies aiming to understand consumer behaviour. The first step is defining a proper measure Read More …

An innovative online process mining framework for supporting incremental GDPR compliance of business processes

Zaman, R., Cuzzocrea, A., & Hassani, M. (2019). An innovative online process mining framework for supporting incremental GDPR compliance of business processes. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), 2019 IEEE International Conference on Big Data, Big Read More …

Designing a Privacy Dashboard for a Smart Manufacturing Environment

Mannhardt, F., Oliveira, M., & Petersen, S. A. (2020). Designing a Privacy Dashboard for a Smart Manufacturing Environment. In I. O. Pappas, I. O. Pappas, P. Mikalef, L. Jaccheri, J. Krogstie, Y. K. Dwivedi, & M. Mäntymäki (Eds.), Digital Transformation for a Sustainable Society in the 21st Century – I3E 2019 IFIP WG 6.11 International Read More …

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 …