Online Prediction Threshold Optimization Under Semi-deferred Labelling

Spenrath, Y., Hassani, M., & van Dongen, B. F. (2024). Online Prediction Threshold Optimization Under Semi-deferred Labelling. In T. Palpanas, & H. V. Jagadish (Eds.), 8th International workshop on Data Analytics solutions for Real-LIfe APplications (DARLI-AP) (CEUR Workshop Proceedings; Vol. 3651). CEUR-WS.org. https://ceur-ws.org/Vol-3651/ Abstract In supermarket loyalty campaigns, shoppers collect stamps to redeem limited-time luxury Read More …

Event Knowledge Graphs for Auditing: A Case Study

Klijn, E. L., Preuss, D., Imeri, L., Baumann, F., Mannhardt, F., & Fahland, D. (2024). Event Knowledge Graphs for Auditing: A Case Study. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 84-97). (Lecture Notes in Business Information Processing; Vol. 503 LNBIP). https://doi.org/10.1007/978-3-031-56107-8_7 Read More …

Implementing Object-Centric Event Data Models in Event Knowledge Graphs

Swevels, A., Fahland, D., & Montali, M. (2024). Implementing Object-Centric Event Data Models in Event Knowledge Graphs. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 431-443). (Lecture Notes in Business Information Processing; Vol. 503 LNBIP). https://doi.org/10.1007/978-3-031-56107-8_33 Abstract Recent advances in object-centric process Read More …

Domain engineering for customer experience management

Benzarti, I., Mili, H., Medeiros de Carvalho, R., & Leshob, A. (2022). Domain engineering for customer experience management. Innovations in Systems and Software Engineering, 18(1), 171-191. https://doi.org/10.1007/s11334-021-00426-2 Abstract Customer experience management (CXM) denotes a set of practices, processes, and tools, that aim at personalizing a customer’s interactions with a company around the customer’s needs and Read More …

An insight to nurse workload: predicting activities in the next shift and analyzing bedside alarms influence

de Carvalho, R. M., Nguyen, H., Heetveld, M., & Luime, J. (2022). An insight to nurse workload: predicting activities in the next shift and analyzing bedside alarms influence. In T. X. Bui (Ed.), Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022 (pp. 4108-4117). IEEE Computer Society. Abstract The effects of Read More …

Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction

Bekelaar, J. W. R., Luime, J. J., & de Carvalho, R. M. (2023). Predicting Patient Care Acuity: An LSTM Approach for Days-to-day Prediction. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 378-390). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_28 Read More …

Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems

Lo Bianco, R., Dijkman, R. M., Nuijten, W. P. M., & van Jaarsveld, W. L. (2023). Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems. In C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management: 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11–15, 2023, Read More …

Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts

Reijnen, R., Zhang, Y., Nuijten, W. P. M., Senaras, C., & Goldak, M. (2021). Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020) (pp. 2647-2654). Article 9308584 IEEE Press. https://doi.org/10.1109/SSCI47803.2020.9308584 Abstract A multi-agent path finding (MAPF) problem is concerned Read More …

Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction

Karetnikov, A., Nuijten, W., & Hassani, M. (2021). Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction. In P. Pezarat-Correia, J. Vilas-Boas, & J. Cabri (Eds.), icSPORTS 2021 – Proceedings of the 9th International Conference on Sport Sciences Research and Technology Support (pp. 43-53). SciTePress Digital Library. Abstract In individual sports, the judgment Read More …

Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems

Mertens, T., & Hassani, M. (2023). Can we Learn from Outliers? Unsupervised Optimization of Intelligent Vehicle Traffic Management Systems. In M.-R. Amini, S. Canu, A. Fischer, T. Guns, P. Kralj Novak, & G. Tsoumakas (Eds.), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part VI Read More …

Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings

Wolters, L., & Hassani, M. (2023). Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 145-157). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). https://doi.org/10.1007/978-3-031-27815-0_11 Abstract Customer journey analysis Read More …

PrefixCDD: Effective Online Concept Drift Detection over Event Streams using Prefix Trees.

Huete, J., Qahtan, A. A., & Hassani, M. (2023). PrefixCDD: Effective Online Concept Drift Detection over Event Streams using Prefix Trees. In H. Shahriar, Y. Teranishi, A. Cuzzocrea, M. Sharmin, D. Towey, AKM. J. A. Majumder, H. Kashiwazaki, J.-J. Yang, M. Takemoto, N. Sakib, R. Banno, & S. I. Ahamed (Eds.), COMPSAC (pp. 328-333) https://doi.org/10.1109/COMPSAC57700.2023.00051 Read More …

An Experiment on Transfer Learning for Suffix Prediction on Event Logs

van Luijken, M., Ketykó, I., & Mannhardt, F. (2024). An Experiment on Transfer Learning for Suffix Prediction on Event Logs. In J. De Weerdt, & L. Pufahl (Eds.), Business Process Management Workshops – BPM 2023 International Workshops, Utrecht, The Netherlands, September 11–15, 2023, Revised Selected Papers (pp. 31-43). (Lecture Notes in Business Information Processing; Vol. 492 LNBIP). Springer. Read More …

Inferring Missing Entity Identifiers from Context Using Event Knowledge Graphs

Swevels, A., Dijkman, R. M., & Fahland, D. (2023). Inferring Missing Entity Identifiers from Context Using Event Knowledge Graphs. In C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management: 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11–15, 2023, Proceedings (pp. 180-197). (Lecture Notes in Computer Science (LNCS); Vol. Read More …

Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach

Mozafari Mehr, A. S., M. de Carvalho, R., & van Dongen, B. (2023). Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 44-56). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Read More …

An Association Rule Mining-Based Framework for the Discovery of Anomalous Behavioral Patterns

Mozafari Mehr, A. S., M. de Carvalho, R., & van Dongen, B. (2022). An Association Rule Mining-Based Framework for the Discovery of Anomalous Behavioral Patterns. In W. Chen, L. Yao, T. Cai, S. Pan, T. Shen, & X. Li (Eds.), Advanced Data Mining and Applications – 18th International Conference, ADMA 2022, Proceedings (pp. 397-412). (Lecture Notes in Computer Read More …

MLA: A Tool for Multi-Perspective Conformance Checking of Business Processes

Mehr, A. S. M., de Carvalho, R. M., & van Dongen, B. (2021). MLA: A Tool for Multi-Perspective Conformance Checking of Business Processes. In ICPM 2021 Doctoral Consortium and Demo Track 2021 (pp. 35-36). (CEUR Workshop Proceedings; Vol. 3098). CEUR-WS.org. https://ceur-ws.org/Vol-3098/demo_200.pdf Abstract Existing conformance checking techniques focus more on the control-flow perspective rather than other Read More …

Aligning Event Logs to Resource-Constrained ν-Petri Nets

Sommers, D., Sidorova, N., & van Dongen, B. (2022). Aligning Event Logs to Resource-Constrained ν-Petri Nets. In L. Bernardinello, & L. Petrucci (Eds.), Application and Theory of Petri Nets and Concurrency – 43rd International Conference, PETRI NETS 2022, Proceedings (pp. 325-345). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Read More …

Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection

Andersen, E., Chiarandini, M., Hassani, M., Janicke, S., Tampakis, P., & Zimek, A. (2022). Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection. In Proceedings – 2022 23rd IEEE International Conference on Mobile Data Management, MDM 2022 (pp. 64-69). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/MDM55031.2022.00030 Abstract Recent approaches have proven the effectiveness Read More …

Aggregating Event Knowledge Graphs for Task Analysis

Klijn, E. L., Mannhardt, F., & Fahland, D. (2023). Aggregating Event Knowledge Graphs for Task Analysis. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 493-505). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_36 Abstract Aggregation of event data is a Read More …

Building User Journey Games from Multi-party Event Logs

Kobialka, P., Mannhardt, F., Tapia Tarifa, S. L., & Johnsen, E. B. (2023). Building User Journey Games from Multi-party Event Logs. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 71-83). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_6 Abstract To Read More …

Early Predicting the Need for Aftercare Based on Patients Events from the First Hours of Stay – A Case Study

Dubbeldam, A. L., Ketykó, I., de Carvalho, R. M., & Mannhardt, F. (2023). Early Predicting the Need for Aftercare Based on Patients Events from the First Hours of Stay – A Case Study. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 366-377). (Lecture Notes in Business Information Processing; Read More …

Discovering an S-Coverable WF-net using DiSCover

Verbeek, H. M. W. (2022). Discovering an S-Coverable WF-net using DiSCover. In A. Burattin, A. Polyvyanyy, & B. Weber (Eds.), Proceedings of the 2022 4th International Conference on Process Mining (ICPM 2022) (pp. 64-71). IEEE Press. https://doi.org/10.1109/ICPM57379.2022.9980723 Abstract Although many algorithms exist that can discover a WF-net from an event log, only a few (if Read More …

Online Prediction of Aggregated Retailer Consumer Behaviour

Spenrath, Y., Hassani, M., & van Dongen, B. F. (2022). Online Prediction of Aggregated Retailer Consumer Behaviour. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops – ICPM 2021 International Workshops, Revised Selected Papers (pp. 211-223). (Lecture Notes in Business Information Processing; Vol. 433 LNBIP). Springer. https://doi.org/10.1007/978-3-030-98581-3_16 Abstract Predicting the behaviour of consumers provides valuable Read More …

BitBooster: Effective Approximation of Distance Metrics via Binary Operations

Spenrath, Y., Hassani, M., & Van Dongen, B. F. (2022). BitBooster: Effective Approximation of Distance Metrics via Binary Operations. In H. Va Leong, S. S. Sarvestani, Y. Teranishi, A. Cuzzocrea, H. Kashiwazaki, D. Towey, J-J. Yang, & H. Shahriar (Eds.), Proceedings – 2022 IEEE 46th Annual Computers, Software, and Applications Conference, COMPSAC 2022 (pp. 201-210). Read More …

Exploring Task Execution Patterns in Event Graphs

Klijn, E. L., Mannhardt, F., & Fahland, D. (2021). Exploring Task Execution Patterns in Event Graphs. In M. Jans, G. Janssenswillen, A. Kalenkova , & F. M. Maggi (Eds.), ICPM 2021 Doctoral Consortium and Demo Track 2021: Proceedings of the ICPM Doctoral Consortium and Demo Track 2021 co-located with 10th International Conference on Process Mining Read More …

Multi-dimensional Process Analysis

Fahland, D. (2022). Multi-dimensional Process Analysis. In C. Di Ciccio, R. Dijkman, A. del Río Ortega, & S. Rinderle-Ma (Eds.), Business Process Management – 20th International Conference, BPM 2022, Proceedings: Lecture Notes in Computer Science (Vol. 13420, pp. 27-33). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Read More …

Discover Context-Rich Local Process Models (Extended Abstract)

Brunings, M., Fahland, D., & Verbeek, E. (2022). Discover Context-Rich Local Process Models (Extended Abstract). In M. Hassani, A. Koschmider, M. Comuzzi, F. M. Maggi, & L. Pufahl (Eds.), ICPM 2022 Doctoral Consortium and Demo Track 2022: Proceedings of the ICPM Doctoral Consortium and Demo Track 2022 (ICPM-D 2022), Bolzano, Italy, October, 2022 (pp. 100-103). Read More …

Defining Meaningful Local Process Models

Brunings, M., Fahland, D., & van Dongen, B. (2022). Defining Meaningful Local Process Models. In M. Koutny, F. Kordon, & D. Moldt (Eds.), Transactions on Petri Nets and Other Models of Concurrency XVI (pp. 24-48). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13220 LNCS). Read More …

Signal Phrase Extraction: Gateway to Information Retrieval Improvement in Law Texts

Sidorova, N., & van der Veen, M. (2021). Signal Phrase Extraction: Gateway to Information Retrieval Improvement in Law Texts. In E. Schweighofer (Ed.), Legal Knowledge and Information Systems – JURIX 2021: The 34th Annual Conference (pp. 127-130). (Frontiers in Artificial Intelligence and Applications; Vol. 346). IOS Press. https://doi.org/10.3233/FAIA210327 Abstract NLP-based techniques can support in improving Read More …

Discovering Care Pathways for Multi-morbid Patients Using Event Graphs

Aali, M. N., Mannhardt, F., & Toussaint, P. J. (2022). Discovering Care Pathways for Multi-morbid Patients Using Event Graphs. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops – ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers. (pp. 352-364). (Lecture Notes in Business Information Processing (LNBIP); Read More …

CPN IDE: An Extensible Replacement for CPN Tools That Uses Access/CPN

Verbeek, E., & Fahland, D. (2021). CPN IDE: An Extensible Replacement for CPN Tools That Uses Access/CPN. In M. Jans, G. Janssenswillen, A. Kalenkova , & F. M. Maggi (Eds.), ICPM 2021 Doctoral Consortium and Demo Track 2021: Proceedings of the ICPM Doctoral Consortium and Demo Track 2021 co-located with 10th International Conference on Process Read More …

Narration as a Technique to Improve Process Model Comprehension: Tell Me What I Cannot See

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 …

Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions

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 …

From Symbolic RPA to Intelligent RPA: Challenges for Developing and Operating Intelligent Software Robots

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 …

Conformance Checking: A Systemic View

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 …

Actionable Conformance Checking: From Intuitions to Code

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 …