@article{MARTIN2020101962,
title = "Recommendations for enhancing the usability and understandability of process mining in healthcare",
journal = "Artificial Intelligence in Medicine",
volume = "109",
pages = "101962",
year = "2020",
issn = "0933-3657",
doi = "https://doi.org/10.1016/j.artmed.2020.101962",
url = "http://www.sciencedirect.com/science/article/pii/S0933365720312276",
author = "Niels Martin and Jochen {De Weerdt} and Carlos Fernández-Llatas and Avigdor Gal and Roberto Gatta and Gema Ibáñez and Owen Johnson and Felix Mannhardt and Luis Marco-Ruiz and Steven Mertens and Jorge Munoz-Gama and Fernando Seoane and Jan Vanthienen and Moe Thandar Wynn and David Baltar Boilève and Jochen Bergs and Mieke Joosten-Melis and Stijn Schretlen and Bart {Van Acker}",
keywords = "Process mining, Healthcare processes, Event log, Process execution data, Health information system, Hospital information system, Process analysis, Process improvement",
abstract = "Healthcare organizations are confronted with challenges including the contention between tightening budgets and increased care needs. In the light of these challenges, they are becoming increasingly aware of the need to improve their processes to ensure quality of care for patients. To identify process improvement opportunities, a thorough process analysis is required, which can be based on real-life process execution data captured by health information systems. Process mining is a research field that focuses on the development of techniques to extract process-related insights from process execution data, providing valuable and previously unknown information to instigate evidence-based process improvement in healthcare. However, despite the potential of process mining, its uptake in healthcare organizations outside case studies in a research context is rather limited. This observation was the starting point for an international brainstorm seminar. Based on the seminar's outcomes and with the ambition to stimulate a more widespread use of process mining in healthcare, this paper formulates recommendations to enhance the usability and understandability of process mining in healthcare. These recommendations are mainly targeted towards process mining researchers and the community to consider when developing a new research agenda for process mining in healthcare. Moreover, a limited number of recommendations are directed towards healthcare organizations and health information systems vendors, when shaping an environment to enable the continuous use of process mining."
}
@article{MARTIN2021101642,
title = "Detection of batch activities from event logs",
journal = "Information Systems",
volume = "95",
pages = "101642",
year = "2021",
issn = "0306-4379",
doi = "https://doi.org/10.1016/j.is.2020.101642",
url = "http://www.sciencedirect.com/science/article/pii/S0306437920301071",
author = "Niels Martin and Luise Pufahl and Felix Mannhardt",
keywords = "Business process, Batch activity, Batch processing, Discovery, Process mining, Batch mining",
abstract = "Organizations carry out a variety of business processes in order to serve their clients. Usually supported by information technology and systems, process execution data is logged in an event log. Process mining uses this event log to discover the process’ control-flow, its performance, information about the resources, etc. A common assumption is that the cases are executed independently of each other. However, batch work – the collective execution of cases for specific activities – is a common phenomenon in operational processes to save costs or time. Existing research has mainly focused on discovering individual batch tasks. However, beyond this narrow setting, batch processing may consist of the execution of several linked tasks. In this work, we present a novel algorithm which can also detect parallel, sequential and concurrent batching over several connected tasks, i.e., subprocesses. The proposed algorithm is evaluated on synthetic logs generated by a business process simulator, as well as on a real-world log obtained from a hospital’s digital whiteboard system. The evaluation shows that batch processing at the subprocess level can be reliably detected."
}
@article{van_zelst_event_2020,
title = {Event abstraction in process mining: literature review and taxonomy},
issn = {2364-4974},
url = {https://doi.org/10.1007/s41066-020-00226-2},
doi = {10.1007/s41066-020-00226-2},
abstract = {The execution of processes in companies generates traces of event data, stored in the underlying information system(s), capturing the actual execution of the process. Analyzing event data, i.e., the focus of process mining, yields a detailed understanding of the process, e.g., we are able to discover the control flow of the process and detect compliance and performance issues. Most process mining techniques assume that the event data are of the same and/or appropriate level of granularity. However, in practice, the data are extracted from different systems, e.g., systems for customer relationship management, Enterprise Resource Planning, etc., record the events at different granularity levels. Hence, pre-processing techniques that allow us to abstract event data into the right level of granularity are vital for the successful application of process mining. In this paper, we present a literature study, in which we assess the state-of-the-art in the application of such event abstraction techniques in the field of process mining. The survey is accompanied by a taxonomy of the existing approaches, which we exploit to highlight interesting novel directions.},
journal = {Granular Computing},
author = {van Zelst, Sebastiaan J. and Mannhardt, Felix and de Leoni, Massimiliano and Koschmider, Agnes},
year = {2020}
}
@inproceedings{DBLP:conf/caise/VoigtFJKTMLW20,
author = {Saskia Nu{\~{n}}ez von Voigt and
Stephan A. Fahrenkrog{-}Petersen and
Dominik Janssen and
Agnes Koschmider and
Florian Tschorsch and
Felix Mannhardt and
Olaf Landsiedel and
Matthias Weidlich},
title = {Quantifying the Re-identification Risk of Event Logs for Process Mining
- Empiricial Evaluation Paper},
booktitle = {CAiSE},
series = {Lecture Notes in Computer Science},
volume = {12127},
pages = {252--267},
publisher = {Springer},
year = {2020}
}
@inproceedings{DBLP:conf/emisa/KoschmiderJM20,
author = {Agnes Koschmider and
Dominik Janssen and
Felix Mannhardt},
title = {Framework for Process Discovery from Sensor Data},
booktitle = {{EMISA}},
series = {{CEUR} Workshop Proceedings},
volume = {2628},
pages = {32--38},
publisher = {CEUR-WS.org},
year = {2020}
}
@inproceedings{DBLP:conf/bpm/0006FKMAW19,
author = {Martin Bauer and
Stephan A. Fahrenkrog{-}Petersen and
Agnes Koschmider and
Felix Mannhardt and
Han van der Aa and
Matthias Weidlich},
title = {ELPaaS: Event Log Privacy as a Service},
booktitle = {{BPM} (PhD/Demos)},
series = {{CEUR} Workshop Proceedings},
volume = {2420},
pages = {159--163},
publisher = {CEUR-WS.org},
year = {2019},
url = {http://ceur-ws.org/Vol-2420/paperDT9.pdf}
}
@article{Michael2019,
author = {Judith Michael and
Agnes Koschmider and
Felix Mannhardt and
Nathalie Baracaldo and
Bernhard Rumpe},
title = {User Centered and Privacy-Driven Process Mining System Design - (Extended
Abstract)},
journal = {Informatik Spektrum},
volume = {42},
number = {5},
year = {2019},
pages = {347--348},
issn="1432-122X",
doi="10.1007/s00287-019-01202-0",
url="https://doi.org/10.1007/s00287-019-01202-0"
}
@InProceedings{deMan2019,
author="de Man, Johannes Cornelis
and Mannhardt, Felix",
editor="Ameri, Farhad
and Stecke, Kathryn E.
and von Cieminski, Gregor
and Kiritsis, Dimitris",
title="Detailed Performance Diagnosis Based on Production Timestamps: A Case Study",
booktitle="Advances in Production Management Systems. Production Management for the Factory of the Future",
year="2019",
publisher="Springer International Publishing",
address="Cham",
pages="708--715",
abstract="This paper demonstrates a detailed performance diagnosis of a production process. With limited investment power for new technologies, managers want to diagnose the reason for system underperformance, i.e. diagnosing performance gaps. This paper found detailed performance measures for specific production orders by using event log data, i.e. a set of timestamps that denote the occurrence of an atomic event in production. Sequential time registrations for each production order give detailed insights in how the production process is behaving. The reported case study gave managers a web application that lets them zoom in and out of different characteristics to get an understanding how their production process results in a certain performance. Based on the background and case, a framework and way forward are proposed on how to perform detailed diagnosis to explain performance gaps in production.",
isbn="978-3-030-30000-5",
doi="10.1007/978-3-030-30000-5_86",
url="https://doi.org/10.1007/978-3-030-30000-5_86
}
@article{Mannhardt2019f,
author = {Felix Mannhardt and
Sobah Abbas Petersen and
Manuel Fradinho Oliveira},
title = {Process Mining and Privacy in Smart Manufacturing},
journal = {Informatik Spektrum},
volume = {42},
number = {5},
pages = {336--339},
year = {2019},
issn="1432-122X",
doi="10.1007/s00287-019-01199-6",
url="https://doi.org/10.1007/s00287-019-01199-6"
}
@article{Mannhardt2019e,
author = {Felix Mannhardt and
Agnes Koschmider and
Nathalie Baracaldo and
Matthias Weidlich and
Judith Michael},
title = {Privacy-preserving Process Mining: Differential - Privacy for Event
Logs (Extended Abstract)},
journal = {Informatik Spektrum},
volume = {42},
number = {5},
pages = {349--351},
year = {2019},
issn="1432-122X",
doi="10.1007/s00287-019-01207-9",
url="https://doi.org/10.1007/s00287-019-01207-9"
}
@InProceedings{Mannhardt.2019d,
author = {Felix Mannhardt and
Manuel Oliveira and
Sobah Abbas Petersen},
title = {Designing a Privacy Dashboard for a Smart Manufacturing Environment},
booktitle = {{I3E} Workshops},
series = {{IFIP} Advances in Information and Communication Technology},
volume = {573},
pages = {79--85},
publisher = {Springer},
year = {2019}
}
@Article{Mannhardt.2019c,
author = {Felix Mannhardt and
Agnes Koschmider and
Nathalie Baracaldo and
Matthias Weidlich and
Judith Michael},
title = {Privacy-Preserving Process Mining - Differential Privacy for Event
Logs},
journal = {Business {\&} Information Systems Engineering},
volume = {61},
number = {5},
pages = {595--614},
year = {2019},
url = {https://doi.org/10.1007/s12599-019-00613-3}
}
@InProceedings{Mannhardt.2019b,
author = {Felix Mannhardt and
Petter Arnesen and
Andreas D. Landmark},
title = {Estimating the Impact of Incidents on Process Delay},
pages = {49--56},
publisher = {{IEEE}},
year = {2019},
booktitle = {International Conference on Process Mining (ICPM 2019)},
doi = {10.1109/ICPM.2019.00018},
url = {https://doi.org/10.1109/ICPM.2019.00018}
}
@Article{Mannhardt.2019a,
author = {Felix Mannhardt and Sobah Abbas Petersen and Manuel Fradinho Oliveira},
title = {A trust and privacy framework for smart manufacturing environments},
journal = {Journal of Ambient Intelligence and Smart Environments},
volume = {11},
number = {3},
year = {2019},
pages = {201--219},
doi = {10.3233/AIS-190521},
url = {https://doi.org/10.3233/AIS-190521}
}
@InProceedings{Michael.2019,
author = {Judith Michael and Agnes Koschmider and Felix Mannhardt and Nathalie Baracaldo and Bernhard Rumpe},
title = {User-Centered and Privacy-Driven Process Mining System Design},
booktitle = {CAiSE Forum 2019},
series = {LNBIP},
publisher = {Springer},
year = {2019},
doi = {10.1007/978-3-030-21297-1_17},
url = {https://doi.org/10.1007/978-3-030-21297-1_17},
volume = {350},
pages = {194--206}
}
@inproceedings{DBLP:conf/ifip5-5/PetersenMOT18,
author = {Sobah Abbas Petersen and
Felix Mannhardt and
Manuel Oliveira and
Hans Torvatn},
title = {A Framework to Navigate the Privacy Trade-offs for Human-Centred Manufacturing},
booktitle = {{PRO-VE}},
series = {{IFIP} Advances in Information and Communication Technology},
volume = {534},
pages = {85--97},
publisher = {Springer},
year = {2018},
url = {https://doi.org/10.1007/978-3-319-99127-6_8},
doi = {10.1007/978-3-319-99127-6_8}
}
@InProceedings{Koschmider.2019,
title={On the Contextualization of Event-Activity Mappings},
author={Agnes Koschmider and Felix Mannhardt and Tobias Heuser},
series = {LNBIP},
publisher = {Springer},
booktitle = {2nd International Workshop on BP-Meet-IoT, Business Process Management Workshops. BPM 2018.},
volume = {342},
pages = {445--457},
year = 2019,
doi = {10.1007/978-3-030-11641-5_35},
url = {https://doi.org/10.1007/978-3-030-11641-5_35}
}
@InProceedings{Mannhardt.2018d,
author = {Felix Mannhardt and Riccardo Bovo and Manuel Fradinho Oliveira and Simon Julier},
title = {A Taxonomy for Combining Activity Recognition and Process Discovery in Industrial Environments},
booktitle = {Intelligent Data Engineering and Automated Learning - IDEAL 2018},
series = {{LNCS}},
volume = {11315},
pages = {84--93},
year = {2018},
publisher = {Springer},
url = {https://doi.org/10.1007/978-3-030-03496-2_10},
doi = {10.1007/978-3-030-03496-2_10}
}
@Article{Mannhardt.2018a,
author = {F. Mannhardt and M. de Leoni and H. A. Reijers and W. M. P. van der Aalst and P. J. Toussaint},
title = {Guided Process Discovery - {A} Pattern-based Approach},
journal = {Information Systems},
url = {https://dx.doi.org/10.1016/j.is.2018.01.009},
doi = {10.1016/j.is.2018.01.009},
volume = {86},
pages = {1--18},
year = {2018}
}
@Article{Mannhardt.2016,
author = {F. Mannhardt and M. de Leoni and H. A. Reijers and W. M. P. van der Aalst},
title = {Balanced multi-perspective checking of process conformance},
journal = {Computing},
year = {2016},
volume = {98},
number = {4},
pages = {407--437},
doi = {10.1007/s00607-015-0441-1},
url = {http://dx.doi.org/10.1007/s00607-015-0441-1},
}
@Inbook{Leoni2018,
author="Massimiliano de Leoni and Felix Mannhardt",
editor="Sakr, Sherif and Zomaya, Albert",
chapter="Decision Discovery in Business Processes",
title="Encyclopedia of Big Data Technologies",
year="2018",
publisher="Springer",
address="Cham",
pages="1--12",
isbn="978-3-319-63962-8",
doi="10.1007/978-3-319-63962-8_96-1",
url="https://doi.org/10.1007/978-3-319-63962-8_96-1"
}
@Misc{Mannhardt.2017f,
author = {F. Mannhardt},
title = {Hospital Billing - Event Log},
year = {2017},
note = {Dataset},
doi = {10.4121/uuid:76c46b83-c930-4798-a1c9-4be94dfeb741},
publisher = {Eindhoven University of Technology},
url = {https://data.4tu.nl/repository/uuid:76c46b83-c930-4798-a1c9-4be94dfeb741},
}
@inproceedings{MANNHARDT2019227,
title = "Mining railway traffic control logs",
journal = "Transportation Research Procedia",
volume = "37",
pages = "227 - 234",
year = "2019",
booktitle = "21st EURO Working Group on Transportation Meeting, EWGT 2018, 17th – 19th September 2018, Braunschweig, Germany",
issn = "2352-1465",
doi = "10.1016/j.trpro.2018.12.187",
url = "https://doi.org/10.1016/j.trpro.2018.12.187",
author = "Felix Mannhardt and Andreas D. Landmark"
}
@InProceedings{Mannhardt.2018c,
title = {Privacy Challenges for Process Mining in Human-centered Industrial Environments},
publisher = {IEEE Xplore},
author = {Felix Mannhardt and Sobah Abbas Petersen and Manuel Fradinho Duarte de Oliveira},
booktitle = {Intelligent Environments ({IE}) 2018},
year = "2018",
pages="64--71",
doi = "10.1109/IE.2018.00017",
url = "https://doi.org/10.1109/IE.2018.00017"
}
@InProceedings{Mannhardt.2018b,
title = {Revealing Work Practices in Hospitals using Process Mining},
publisher = {IOS Press},
year = {2018},
pages = {281--285},
doi = {10.3233/978-1-61499-852-5-281},
series = {Studies in Health Technology and Informatics},
author = {Felix Mannhardt and Pieter J. Toussaint},
booktitle = {Medical Informatics Europe ({MIE}) 2018},
url = {https://dx.doi.org/10.3233/978-1-61499-852-5-281}
}
@InProceedings{Dees.2017,
pages = {232--251},
title = {Enhancing Process Models to Improve Business Performance: A Methodology and Case Studies},
publisher = {Springer},
year = {2017},
author = {Dees, Marcus and de Leoni, Massimiliano and Mannhardt, Felix},
isbn = {978-3-319-69462-7},
booktitle = {{CoopIS} 2017},
doi = {10.1007/978-3-319-69462-7_15},
url = {https://doi.org/10.1007/978-3-319-69462-7_15}
}
@InProceedings{Mannhardt.2017e,
author = {Felix Mannhardt and Massimiliano de Leoni and Hajo A. Reijers},
title = {Heuristic Mining Revamped: An Interactive Data-aware and Conformance-aware Miner},
booktitle = {{BPM} 2017 Demos},
year = {2017},
pages = {1--5},
volume = {1920},
series = {{CEUR} Workshop Proceedings},
publisher = {CEUR-WS.org},
url = {http://ceur-ws.org/Vol-1920/BPM_2017_paper_167.pdf},
}
@InProceedings{Mannhardt.2017d,
author = {F. Mannhardt and M. de Leoni and H. A. Reijers and W. M. P. van der Aalst and P. J. Toussain},
title = {From Low-Level Events to Activities - A Pattern-based Approach (Extended Abstract)},
booktitle = {EMISA 2017},
series = {Mitteilungen der GI-Fachgruppe Entwicklungsmethoden für Informationssysteme und deren Anwendung},
volume = {37},
number = {1},
year = {2017},
pages = {47--48},
url = {http://www.emisa.org/index.php/publikationen/forum/item/77-2017-1}
}
@InProceedings{Mannhardt.2017c,
author = {F. Mannhardt and N. Tax},
title = {Unsupervised Event Abstraction using Pattern Abstraction and Local Process Models},
booktitle = {RADAR+EMISA 2017},
series = {CEUR Workshop Proceedings},
pages = {55--63},
url = {http://ceur-ws.org/Vol-1859/bpmds-06-paper.pdf},
year = "2017",
volume = {1859},
publisher = {CEUR-WS.org}
}
@InProceedings{Mannhardt.2017b,
author = {F. Mannhardt and D. Blinde},
title = {Analyzing the Trajectories of Patients with Sepsis using Process Mining},
booktitle = {RADAR+EMISA 2017},
series = {CEUR Workshop Proceedings},
pages = {72--80},
url = {http://ceur-ws.org/Vol-1859/bpmds-08-paper.pdf},
year = "2017",
volume = {1859},
publisher = {CEUR-WS.org}}
@InProceedings{Mannhardt2017,
author = {F. Mannhardt and
M. de Leoni and
H. A. Reijers and
W. M. P. van der Aalst},
title="Data-Driven Process Discovery - Revealing Conditional Infrequent Behavior from Event Logs",
booktitle = {CAiSE 2017},
series = {LNCS},
volume = {10253},
year="2017",
publisher="Springer ",
pages="545--560",
doi="10.1007/978-3-319-59536-8_34",
url={http://dx.doi.org/10.1007/978-3-319-59536-8_34}
}
@InProceedings{Mannhardt.2016d,
author = {F. Mannhardt and M. de Leoni and H. A. Reijers and W. M. P. van der Aalst and P. J. Toussaint},
title = {From Low-Level Events to Activities - {A} Pattern-Based Approach},
booktitle = {{BPM} 2016},
year = {2016},
editor = {Marcello La Rosa and Peter Loos and Oscar Pastor},
volume = {9850},
series = {LNCS},
pages = {125--141},
publisher = {Springer},
doi = {10.1007/978-3-319-45348-4_8},
url = {http://dx.doi.org/10.1007/978-3-319-45348-4_8},
}
@InProceedings{Mannhardt.2016b,
author = {F. Mannhardt and M. de Leoni and H. A. Reijers and W. M. P. van der Aalst},
title = {Decision Mining Revisited - Discovering Overlapping Rules},
booktitle = {CAiSE 2016},
year = {2016},
editor = {Selmin Nurcan and Pnina Soffer and Marko Bajec and Johann Eder},
volume = {9694},
series = {LNCS},
pages = {377--392},
publisher = {Springer},
doi = {10.1007/978-3-319-39696-5_23},
url = {http://dx.doi.org/10.1007/978-3-319-39696-5_23},
}
@InProceedings{Mannhardt.2015,
author = {F. Mannhardt and M. de Leoni and H. A. Reijers and W. M. P. van der Aalst},
title = {Measuring the Precision of Multi-perspective Process Models},
booktitle = {{BPM} 2015 Workshops},
year = {2015},
editor = {Manfred Reichert and Hajo A. Reijers},
volume = {256},
series = {LNBIP},
pages = {113--125},
publisher = {Springer},
doi = {10.1007/978-3-319-42887-1_10},
url = {http://dx.doi.org/10.1007/978-3-319-42887-1_10},
}
@InProceedings{Mannhardt.2015a,
author = {F. Mannhardt and M. de Leoni and H. A. Reijers},
title = {The Multi-perspective Process Explorer},
booktitle = {{(BPM} 2015) Demos},
year = {2015},
editor = {Florian Daniel and Stefan Zugal},
volume = {1418},
series = {{CEUR} Workshop Proceedings},
pages = {130--134},
publisher = {CEUR-WS.org},
url = {http://ceur-ws.org/Vol-1418/paper27.pdf},
}
@InProceedings{Aa.2015,
author = {H. van der Aa and H. Leopold and F. Mannhardt and H. A. Reijers},
title = {On the Fragmentation of Process Information: Challenges, Solutions, and Outlook},
booktitle = {BPMDS 2015},
year = {2015},
editor = {Khaled Gaaloul and Rainer Schmidt and Selmin Nurcan and S{\'{e}}rgio Guerreiro and Qin Ma},
volume = {214},
series = {LNBIP},
pages = {3--18},
publisher = {Springer},
doi = {10.1007/978-3-319-19237-6_1},
url = {http://dx.doi.org/10.1007/978-3-319-19237-6_1},
}
@InProceedings{Mannhardt.2014a,
author = {F. Mannhardt and M. de Leoni and H. A. Reijers},
title = {Extending Process Logs with Events from Supplementary Sources},
booktitle = {{BPM} 2014 Workshops},
year = {2014},
editor = {Fabiana Fournier and Jan Mendling},
volume = {202},
series = {LNBIP},
pages = {235--247},
publisher = {Springer},
doi = {10.1007/978-3-319-15895-2_21},
url = {http://dx.doi.org/10.1007/978-3-319-15895-2_21},
}
@InProceedings{Mannhardt.2013,
author = {F. Mannhardt},
title = {Web-based Editor for {YAWL}},
booktitle = {Proceedings of the First {YAWL} Symposium, Sankt Augustin, Germany, June 7, 2013},
year = {2013},
editor = {Thomas Freytag and Andreas Hense and Arthur H. M. ter Hofstede and Jan Mendling},
volume = {982},
series = {{CEUR} Workshop Proceedings},
pages = {62--68},
publisher = {CEUR-WS.org},
url = {http://ceur-ws.org/Vol-982/YAWL2013-Paper09.pdf},
}
@InProceedings{Ekanayake.2012,
author = {C. C. Ekanayake and F. Mannhardt and L. García-Bañuelos and M. La Rosa and M. Dumas and A. H. M. ter Hofstede},
title = {Detecting Approximate Clones in Process Model Repositories with Apromore},
booktitle = {{(BPM} 2012) Demos},
year = {2012},
editor = {Niels Lohmann and Simon Moser},
volume = {940},
series = {{CEUR} Workshop Proceedings},
pages = {29--33},
publisher = {CEUR-WS.org},
url = {http://ceur-ws.org/Vol-940/paper6.pdf},
}
@TechReport{Mannhardt.2016g,
author = {F Mannhardt},
title = {XESLite - Managing Large XES Event Logs in ProM},
institution = {BPMCenter.org},
year = {2016},
type = {BPM Center Report},
number = {BPM-16-04},
url = {http://bpmcenter.org/wp-content/uploads/reports/2016/BPM-16-04.pdf},
}
@TechReport{Verbeek.2016,
author = {H.M.W. Verbeek and F. Mannhardt},
title = {The DrFurby Classifier submission to the Process Discovery Contest @ BPM 2016},
institution = {BPMCenter.org},
year = {2016},
type = {BPM Center Report},
number = {BPM-16-08},
url = {http://bpmcenter.org/wp-content/uploads/reports/2016/BPM-16-08.pdf},
}
@TechReport{Mannhardt.2016e,
author = {F Mannhardt and M de Leoni and H A Reijers and W M P van der Aalst and P J Toussaint},
title = {From Low-Level Events to Activities - A Pattern-based Approach},
institution = {BPMCenter.org},
year = {2016},
type = {BPM Center Report},
number = {BPM-16-02},
url = {http://bpmcenter.org/wp-content/uploads/reports/2016/BPM-16-02.pdf},
}
@TechReport{Mannhardt.2016c,
author = {F Mannhardt and M de Leoni and H A Reijers and W M P van der Aalst},
title = {Decision Mining Revisited - Discovering Overlapping Rules},
institution = {BPMcenter.org},
year = {2016},
type = {BPM Center Report},
number = {BPM-16-01},
url = {http://bpmcenter.org/wp-content/uploads/reports/2016/BPM-16-01.pdf},
}
@TechReport{Mannhardt.2014,
author = {F. Mannhardt, M. de Leoni, H.A Reijers and W.M.P. van der Aalst},
title = {Balanced Multi-Perspective Checking of Process Conformance},
institution = {BPMcenter.org},
year = {2014},
type = {BPM Center Report},
number = {BPM-14-07},
url = {http://bpmcenter.org/wp-content/uploads/reports/2014/BPM-14-07.pdf},
}
@Misc{Leoni.2015,
author = {M. de Leoni and F. Mannhardt},
title = {Road Traffic Fine Management Process},
year = {2015},
note = {Dataset},
doi = {10.4121/uuid:270fd440-1057-4fb9-89a9-b699b47990f5},
publisher = {Eindhoven University of Technology},
url = {http://dx.doi.org/10.4121/uuid:270fd440-1057-4fb9-89a9-b699b47990f5},
}
@Misc{Mannhardt.2016f,
author = {F. Mannhardt},
title = {Sepsis Cases - Event Log},
year = {2016},
note = {Dataset},
doi = {10.4121/uuid:915d2bfb-7e84-49ad-a286-dc35f063a460},
publisher = {Eindhoven University of Technology},
url = {http://dx.doi.org/10.4121/uuid:915d2bfb-7e84-49ad-a286-dc35f063a460},
}
@Misc{Mannhardt.2016a,
author = {F. Mannhardt},
title = {Data-driven Process Discovery - Artificial Event Log},
year = {2016},
note = {Dataset},
doi = {10.4121/uuid:32cad43f-8bb9-46af-8333-48aae2bea037},
publisher = {Eindhoven University of Technology},
url = {https://doi.org/10.4121/uuid:32cad43f-8bb9-46af-8333-48aae2bea037},
}