Conference contribution

Privacy Challenges for Process Mining in Human-Centered Industrial Environments

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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

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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

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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

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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

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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

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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?

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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 …

A general framework to identify software components from execution data

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Liu, C., van Dongen, B. F., Assy, N., & van der Aalst, W. M. P. (2019). A general framework to identify software components from execution data. In G. Spanoudakis, E. Damiani, L. Maciaszek, & L. Maciaszek (Eds.), ENASE 2019 – Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering (pp. Read More …

A framework to evaluate and compare decision-mining techniques

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Jouck, T., de Leoni, M., & Depaire, B. (2019). A framework to evaluate and compare decision-mining techniques. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops – BPM 2018 International Workshops, Revised Papers (pp. 482-493). (Lecture Notes in Business Information Processing; Vol. 342). Cham: Springer. DOI: 10.1007/978-3-030-11641-5_38 Abstract During the Read More …

Software architectural model discovery from execution data

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Liu, C., van Dongen, B. F., Assy, N., & van der Aalst, W. M. P. (2018). Software architectural model discovery from execution data. In ENASE 2018 – Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering (pp. 3-10) Abstract During the execution of software systems, many crashes and exceptions may Read More …

Multi-perspective process mining

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Mannhardt, F. (2018). Multi-perspective process mining. In W. van den Aalst, F. Casati, R. Conforti, M. de Leoni, M. Dumas, A. Kumar, J. Mendling, S. Nepal, B. Pentland, … B. Weber (Eds.), Proceedings of the Dissertation Award, Demonstration, and Industrial Track at BPM 2018: Sydney, Australia, September 9-14, 2018. (pp. 41-45). (CEUR Workshop Proceedings; No. Read More …

Mining local process models with constraints efficiently: applications to the analysis of smart home data

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Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Mining local process models with constraints efficiently: applications to the analysis of smart home data. In Proceedings of the 14th International Conference on Intelligent Environments (IE) (pp. 56-63). [8595032] Piscataway: Institute of Electrical and Electronics Engineers. DOI: 10.1109/IE.2018.00016 Abstract Sequential pattern Read More …

Effective steering of customer journey via order-aware recommendation

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Goossens, J. A. J., Demewez, T., & Hassani, M. (2018). Effective steering of customer journey via order-aware recommendation. In 2018 IEEE International Conference on Data Mining Workshops (ICDMW) (pp. 828-837). Piscataway: Institute of Electrical and Electronics Engineers. DOI: 10.1109/ICDMW.2018.00123 Abstract The analysis of customer journeys is a subject undergoing an intense study recently . The Read More …

Dealing with artifact-centric systems: a process mining approach

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Li, G., & de Carvalho, R. M. (2018). Dealing with artifact-centric systems: a process mining approach. In M. Fellmann, & K. Sandkuhl (Eds.), Proceedings of the 9th International Workshop on Enterprise Modeling and Information Systems Architectures (EMISA 2018): Rostock, Germany, May 24th to 25th, 2018. (pp. 80-84). (CEUR Workshop Proceedings; Vol. 2097). CEUR-WS.org. Abstract Process Read More …

Alarm-based prescriptive process monitoring

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Teinemaa, Irene, Tax, Niek, de Leoni, Massimiliano, Dumas, Marlon & Maggi, Fabrizio Maria (2018). Alarm-based prescriptive process monitoring. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management Forum – BPM Forum 2018, Proceedings (pp. 91-107). (Lecture Notes in Business Information Processing, No. 329). Springer. Abstract Predictive process monitoring is Read More …

Configurable event correlation for process discovery from object-centric event data

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Li, Guangming, Medeiros De Carvalho, Renata & van der Aalst, Wil M.P. (2018). Configurable event correlation for process discovery from object-centric event data. Proceedings – 2018 IEEE International Conference on Web Services, ICWS 2018 – Part of the 2018 IEEE World Congress on Services (pp. 203-210). Institute of Electrical and Electronics Engineers (IEEE). Abstract Many Read More …

Indulpet miner : combining discovery algorithms

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Leemans, Sander J.J., Tax, Niek & ter Hofstede, Arthur H.M. (2018). Indulpet miner : combining discovery algorithms. In Dumitru Roman, Henderik A. Proper, Robert Meersman, Hervé Panetto, Christophe Debruyne & Claudio Agostino Ardagna (Eds.), On the Move to Meaningful Internet Systems. OTM 2018 Conferences – Confederated International Conferences (pp. 97-115). (Lecture Notes in Computer Science Read More …