Log skeletons: a classification approach to process discovery

Verbeek, H. M. W., & Medeiros de Carvalho, R. (2018). Log skeletons: a classification approach to process discovery. arXiv.org. http://arxiv.org/abs/1806.08247 Abstract To test the effectiveness of process discovery algorithms, a Process Discovery Contest (PDC) has been set up. This PDC uses a classification approach to measure this effectiveness: The better the discovered model can classify Read More …

Mining process model descriptions of daily life through event abstraction

Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Mining process model descriptions of daily life through event abstraction. In S. Kapoor, R. Bhatia, & Y. Bi (Eds.), Intelligent Systems and Applications: Extended and Selected Results from the SAI Intelligent Systems Conference (IntelliSys) 2016 (pp. 83-104). (Studies in Computational Intelligence; 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 …

A Framework to Navigate the Privacy Trade-offs for Human-Centred Manufacturing

Petersen, S. A., Mannhardt, F., Oliveira, M., & Torvatn, H. (2018). A Framework to Navigate the Privacy Trade-offs for Human-Centred Manufacturing. In Y. Rezgui, H. Afsarmanesh, & L. M. Camarinha-Matos (Eds.), Collaborative Networks of Cognitive Systems – 19th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2018, Proceedings (pp. 85-97). (IFIP Advances in Information 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 …

Conformance checking: relating processes and models, relating processes and models

Carmona, J., van Dongen, B., Solti, A., & Weidlich, M. (2018). Conformance checking: relating processes and models. Springer International Publishing Switzerland. https://doi.org/10.1007/978-3-319-99414-7 Abstract This book introduces readers to the field of conformance checking as a whole and outlines the fundamental relation between modelled and recorded behaviour. Conformance checking interrelates the modelled and recorded behaviour of 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 …

Computing alignments of event data and process models

van Zelst, S. J., Bolt, A., & van Dongen, B. F. (2018). Computing alignments of event data and process models. In M. Koutny, L. M. Kristensen, & W. Penczek (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIII (pp. 1-26). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and 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 …

Software architectural model discovery from execution data

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

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

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

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

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 …

Native directly follows operator

Syamsiyah, A., Dongen, B. F. van, & Dijkman, R. M. (2018). Native directly follows operator. arXiv. Abstract Typical legacy information systems store data in relational databases. Process mining is a research discipline that analyzes this data to obtain insights into processes. Many different process mining techniques can be applied to data. In current techniques, an Read More …

Alarm-based prescriptive process monitoring

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

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

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 …

Software process analysis methodology-a methodology based on lessons learned in embracing legacy software

Leemans, Maikel, van der Aalst, Wil M.P., van den Brand, Mark G.J., Schiffelers, Ramon R.H. & Lensink, Leonard (2018). Software process analysis methodology-a methodology based on lessons learned in embracing legacy software. Proceedings – 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018 (pp. 665-674). Piscataway: Institute of Electrical and Electronics Engineers (IEEE). Read More …

Lifecycle-Based Process Performance Analysis

Hompes, Bart F.A. & van der Aalst, Wil M.P. (2018). Lifecycle-Based Process Performance Analysis. 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. 336-353). (Lecture Notes in Computer Science (including subseries Lecture Read More …

Analyzing customer journey with process mining : from discovery to recommendations

Terragni, Alessandro & Hassani, Marwan (2018). Analyzing customer journey with process mining : from discovery to recommendations. In Muhammad Younas & Jules Pagna Disso (Eds.), Proceedings – 2018 IEEE 6th International Conference on Future Internet of Things and Cloud, FiCloud 2018 (pp. 224-229). Piscataway: Institute of Electrical and Electronics Engineers (IEEE). Abstract Customer journey analysis Read More …

Efficiently computing alignments : using the extended marking equation

Dongen, Boudewijn F. van (2018). Efficiently computing alignments : using the extended marking equation. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management – 16th International Conference, BPM 2018, Proceedings (pp. 197-214). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Read More …

Fast conformance analysis based on activity log abstraction

Dixit, P.M. & van der Aalst, W.M.P. (2018). Fast conformance analysis based on activity log abstraction. 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference, Proceedings (pp. 135-144). Piscataway. Abstract Process mining techniques focus on bridging the gap between activity logs and business process management. Process discovery is a sub-field of process mining which uses Read More …

Incremental computation of synthesis rules for free-choice Petri nets

Dixit, Prabhakar M., Verbeek, H.M.W. & van der Aalst, Wil M.P. (2018). Incremental computation of synthesis rules for free-choice Petri nets. In Peter Csaba Ölveczky & Kyungmin Bae (Eds.), Formal Aspects of Component Software – 15th International Conference, FACS 2018, Proceedings (pp. 97-117). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence Read More …

Interactive data-driven process model construction

Dixit, P. M., Verbeek, H.M.W., Buijs, J. C.A.M. & van der Aalst, W. M.P. (2018). Interactive data-driven process model construction. In Xiaoyong Du, Guoliang Li, Zhanhuai Li, Juan C. Trujillo, Tok Wang Ling, Karen C. Davis & Mong Li Lee (Eds.), Conceptual Modeling – 37th International Conference, ER 2018, Proceedings (pp. 251-265). (Lecture Notes in Read More …

The performance spectrum miner : visual analytics for fine-grained performance analysis of processes

Denisov, Vadim, Belkina, Elena, Fahland, Dirk & van der Aalst, Wil M.P. (2018). The performance spectrum miner : visual analytics for fine-grained performance analysis of processes. CEUR Workshop Proceedings, 2196, 96-100. Abstract We present the Performance Spectrum Miner, a ProM plugin, which implements a new technique for fine-grained performance analysis of processes. The technique uses Read More …

Aligning partially-ordered process-execution traces and models using automated planning

de Leoni, Massimiliano, Lanciano, Giacomo & Marrella, Andrea (2018). Aligning partially-ordered process-execution traces and models using automated planning. 28th International Conference on Automated Planning and Scheduling, ICAPS 2018 (pp. 321-329). (Proceedings International Conference on Automated Planning and Scheduling, ICAPS). Abstract Conformance checking is the problem of verifying if the actual executions of business processes, which Read More …

A holistic approach for soundness verification of decision-aware process models

de Leoni, Massimiliano, Felli, Paolo & Montali, Marco (2018). A holistic approach for soundness verification of decision-aware process models. In Xiaoyong Du, Guoliang Li, Zhanhuai Li, Juan C. Trujillo, Tok Wang Ling, Karen C. Davis & Mong Li Lee (Eds.), Conceptual Modeling – 37th International Conference, ER 2018, Proceedings (pp. 219-235). (Lecture Notes in Computer Read More …

Towards effective generation of synthetic memory references via markovian models

Cuzzocrea, Alfredo, Mumolo, Enzo, Hassani, Marwan & Grasso, Giorgio Mario (2018). Towards effective generation of synthetic memory references via markovian models. In Ling Liu, Claudio Demartini, Ji-Jiang Yang, Thomas Conte, Kamrul Hasan, Edmundo Tovar, Zhiyong Zhang, Sheikh Iqbal Ahamed, Stelvio Cimato, Toyokazu Akiyama, Sorel Reisman, William Claycomb, Motonori Nakamura, Hiroki Takakura & Chung-Horng Lung (Eds.), Read More …

A Markov-Model-based framework for supporting real-time generation of synthetic memory references effectively and efficiently

Cuzzocrea, Alfredo, Mumolo, Enzo, Hassani, Marwan & Grasso, Giorgio Mario (2018). A Markov-Model-based framework for supporting real-time generation of synthetic memory references effectively and efficiently. Proceedings – DMSVIVA 2018 (pp. 83-90). Pittsburgh: Knowledge Systems Institute Graduate School. Abstract Driven by several real-life case studies and in-lab developments, synthetic memory reference generation has a long tradition Read More …

Online conformance checking using behavioural patterns

Burattin, Andrea, van Zelst, Sebastiaan J., Armas-Cervantes, Abel, van Dongen, Boudewijn F. & Carmona, Josep (2018). Online conformance checking using behavioural patterns. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management – 16th International Conference, BPM 2018, Proceedings (pp. 250-267). (Lecture Notes in Computer Science (including subseries Lecture Notes Read More …

Who is behind the model? classifying modelers based on pragmatic model features

Burattin, Andrea, Soffer, Pnina, Fahland, Dirk, Mendling, Jan, Reijers, Hajo A., Vanderfeesten, Irene, Weidlich, Matthias & Weber, Barbara (2018). Who is behind the model? classifying modelers based on pragmatic model features. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management – 16th International Conference, BPM 2018, Proceedings (pp. 322-338). Read More …

Maximizing synchronization for aligning observed and modelled behaviour

Bloemen, Vincent, van Zelst, Sebastiaan J., van der Aalst, Wil M.P., van Dongen, Boudewijn F. & van de Pol, Jaco (2018). Maximizing synchronization for aligning observed and modelled behaviour. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management – 16th International Conference, BPM 2018, Proceedings (pp. 233-249). (Lecture Notes Read More …

Optimal deployment of configurable business processes in cloud federations

Rekik, Molka, Boukadi, Khouloud, Assy, Nour, Gaaloul, Walid & Ben-Abdallah, Hanene (2018). Optimal deployment of configurable business processes in cloud federations. IEEE Transactions on Network and Service Management, Abstract Configurable processes are increasingly being adopted by enterprises that seek experience sharing and best practice adoption. A configurable process is a customizable model that specifies how Read More …

Analysing structured learning behaviour in Massive Open Online Courses (MOOCs) : An approach based on process mining and clustering

Beemt, A.A.J. van den, Buijs, J.C.A.M. & Aalst, W.M.P. van der (2018). Analysing structured learning behaviour in Massive Open Online Courses (MOOCs) : An approach based on process mining and clustering. International Review of Research in Open and Distance Learning, 19(5), 38-60. Abstract The increasing use of digital systems to support learning leads to a Read More …