Aysolmaz, B., Cayhani, F. N., & Reijers, H. A. (Accepted/In press). Narration as a Technique to Improve Process Model Comprehension: Tell Me What I Cannot See. In Proceedings of the 34th International Conference on Advanced Information Systems Engineering (CAiSE’22) Abstract Conceptual models play a vital role in the engineering of information systems. A variety of Read More …
Koorn, J. J., Lu, X., Mannhardt, F., Leopold, H., & Reijers, H. A. (2022). Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions. https://doi.org/10.24251/HICSS.2022.503 Abstract Process mining is a family of techniques that can aid healthcare organizations in improving their processes. Most existing process mining techniques do not provide insights Read More …
Herm, L. V., Janiesch, C., Reijers, H. A., & Seubert, F. (2021). From Symbolic RPA to Intelligent RPA: Challenges for Developing and Operating Intelligent Software Robots. In A. Polyvyanyy, M. T. Wynn, A. Van Looy, & M. Reichert (Eds.), Business Process Management – 19th International Conference, BPM 2021, Proceedings (pp. 289-305). (Lecture Notes in Computer Read More …
Dongen, B. F. V. (2022). Conformance Checking: A Systemic View. In A. Marrella, & B. Weber (Eds.), Business Process Management Workshops – BPM 2021 International Workshops, Revised Selected Papers (pp. 61-72). (Lecture Notes in Business Information Processing; Vol. 436 LNBIP). https://doi.org/10.1007/978-3-030-94343-1_5 Abstract Within the field of process mining, conformance checking plays an important role. While Read More …
Carmona, J., Weidlich, M., & Dongen, B. V. (2020). Actionable Conformance Checking: From Intuitions to Code. In R-D. Kutsche, & E. Zimányi (Eds.), Big Data Management and Analytics – 9th European Summer School, eBISS 2019, Revised Selected Papers (pp. 1-24). (Lecture Notes in Business Information Processing; Vol. 390). Springer. https://doi.org/10.1007/978-3-030-61627-4_1 Abstract Conformance checking is receiving Read More …
Sommers, D., Menkovski, V., & Fahland, D. (2021). Process Discovery Using Graph Neural Networks. In C. Di Ciccio, C. Di Francescomarino, & P. Soffer (Eds.), Proceedings – 2021 3rd International Conference on Process Mining, ICPM 2021 (pp. 40-47) https://doi.org/10.1109/ICPM53251.2021.9576849 Abstract Automatically discovering a process model from an event log is the prime problem in process Read More …
Brons, D., Scheepens, R., & Fahland, D. (2021). Striking a new Balance in Accuracy and Simplicity with the Probabilistic Inductive Miner. In C. Di Ciccio, C. Di Francescomarino, & P. Soffer (Eds.), Proceedings – 2021 3rd International Conference on Process Mining, ICPM 2021 (pp. 32-39) https://doi.org/10.1109/ICPM53251.2021.9576864 Abstract Numerous process discovery techniques exist for generating process Read More …
Mozafari Mehr, A., Medeiros de Carvalho, R., & van Dongen, B. F. (2021). Detecting Privacy, Data and Control-Flow Deviations in Business Processes. In S. Nurcan, & A. Korthaus (Eds.), Intelligent Information Systems – CAiSE Forum 2021, Proceedings (pp. 82-91). (Lecture Notes in Business Information Processing; Vol. 424 LNBIP). Springer. https://doi.org/10.1007/978-3-030-79108-7_10 Abstract Existing access control mechanisms Read More …
Lövei, P., Nazarchuk, I., Aslam, S., Yu, B., Megens, C. J. P. G., & Sidorova, N. (2021). Designing Micro-intelligences for Situated Affective Computing. In R-H. Liang, A. Chiumento, P. Pawełczak, & M. Funk (Eds.), CHIIOT 2021: Workshops on Computer Human Interaction in IoT Applications Abstract In this position paper we show how micro-intelligences can be Read More …
Hassani, M., & Habets, S. (2021). Predicting Next Touch Point In A Customer Journey – A Use Case In Telecommunication. In 35th ECMS INTERNATIONAL CONFERENCE ON MODELLING AND SIMULATION (1 ed., Vol. 35, pp. 48-54). (Proceedings – European Council for Modelling and Simulation, ECMS). https://doi.org/10.7148/2021-0048 Abstract Customer journey analysis is rapidly increasing in popularity, as Read More …
Klijn, E. L., Mannhardt, F., & Fahland, D. (2021). Classifying and Detecting Task Executions and Routines in Processes Using Event Graphs. In A. Polyvyanyy, M. T. Wynn, A. Van Looy, & M. Reichert (Eds.), Business Process Management Forum, BPM 2021, Proceedings (pp. 212-229). (Lecture Notes in Business Information Processing; Vol. 427 LNBIP). https://doi.org/10.5281/zenodo.5091610, https://doi.org/10.1007/978-3-030-85440-9_13 Abstract Business Read More …
Syamsiyah, A., & Leemans, S. J. J. (2020). Process discovery using in-database minimum self distance abstractions. In 35th Annual ACM Symposium on Applied Computing, SAC 2020 (pp. 26-35). Association for Computing Machinery, Inc. https://doi.org/10.1145/3341105.3373846 Abstract Process executions generate event data that are typically stored in legacy information systems, such as databases. However, process discovery, which Read More …
Beerepoot, I., Ouali, A., van de Weerd, I., & Reijers, H. A. (2020). Working around health information systems: To accept or not to accept? In J. vom Brocke, S. Gregor, & O. Muller (Eds.), 27th European Conference on Information Systems – Information Systems for a Sharing Society, ECIS 2019 [182] Association for Information Systems. https://aisel.aisnet.org/ecis2019_rp/182 Read More …
Beerepoot, I., van de Weerd, I., & Reijers, H. A. (2019). The potential of workarounds for improving processes. In C. Di Francescomarino, R. Dijkman, & U. Zdun (Eds.), Business Process Management Workshops – BPM 2019 International Workshops, Revised Selected Papers (pp. 338-350). (Lecture Notes in Business Information Processing; Vol. 362 LNBIP). Springer. https://doi.org/10.1007/978-3-030-37453-2_28 Abstract Several Read More …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
Spenrath, Y., Hassani, M., van Dongen, B. F., & Tariq, H. Why did my Consumer Shop? Learning an Efficient Distance Metric for Retailer Transaction Data. In Y. Dong, D. Mladenic, & C. Saunders (Eds.), Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track – European Conference, ECML PKDD 2020, Proceedings (pp. Read More …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
