2019

Selecting a process variant modeling approach: guidelines and application

Posted onAuthorEric VerbeekLeave a comment

Aysolmaz, B., Schunselaar, D. M. M., Reijers, H. A., & Yaldiz, A. (2019). Selecting a process variant modeling approach: guidelines and application. Software and Systems Modeling, 18(2), 1155-1178. https://doi.org/10.1007/s10270-017-0648-z Abstract Various modeling approaches have been introduced to manage process diversity in a business context. For practitioners, it is difficult to select an approach suitable for Read More …

The potential of workarounds for improving processes

Posted onAuthorEric VerbeekLeave a comment

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 …

Using graph data structures for event logs

Posted onAuthorEric VerbeekLeave a comment

Esser, S., & Fahland, D. (2019). Using graph data structures for event logs. https://doi.org/10.5281/zenodo.3333831 Abstract Process mining as described in by Wil van der Aalst in is a combination of data mining and business process management to a new discipline. The general purpose of process mining is to derive process insights from event data captured Read More …

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

Posted onAuthorEric VerbeekLeave a comment

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 …

A trust and privacy framework for smart manufacturing environments

Posted onAuthorEric VerbeekLeave a comment

Mannhardt, F., Petersen, S. A., & Oliveira, M. F. (2019). A trust and privacy framework for smart manufacturing environments. Journal of Ambient Intelligence and Smart Environments, 11(3), 201-219. https://doi.org/10.3233/AIS-190521 Abstract Operators in industrial manufacturing environments are under pressure to cope with the ever increasing flexibility and complexity of work. Transitioning towards data-driven smart manufacturing environments Read More …

Detailed Performance Diagnosis Based on Production Timestamps: A Case Study

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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 …

Privacy-Preserving Process Mining: Differential Privacy for Event Logs

Posted onAuthorEric VerbeekLeave a comment

Mannhardt, F., Koschmider, A., Baracaldo, N., Weidlich, M., & Michael, J. (2019). Privacy-Preserving Process Mining: Differential Privacy for Event Logs. Business and Information Systems Engineering, 61(5), 595-614. https://doi.org/10.1007/s12599-019-00613-3 Abstract Privacy regulations for data can be regarded as a major driver for data sovereignty measures. A specific example for this is the case of event data Read More …

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

Posted onAuthorEric VerbeekLeave a comment

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 …

Connecting databases with process mining: a meta model and toolset

Posted onAuthorEric VerbeekLeave a comment

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 …

A tour in process mining: from practice to algorithmic challenges

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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 …

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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 …

What if process predictions are not followed by good recommendations?

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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

Posted onAuthorEric VerbeekLeave a comment

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 …