Publications 2010

  • [PDF] [DOI] W. M. P. van der Aalst, V. Rubin, H. M. W. Verbeek, B. F. van Dongen, E. Kindler, and C. W. G√ľnther, “Process mining: a two-step approach to balance between underfitting and overfitting,” Software and systems modeling (sosym), vol. 9, iss. 1, pp. 87-111, 2010.
    [Bibtex]
    @Article{Aalst10,
    Title = {Process Mining: A Two-Step Approach to Balance Between Underfitting and Overfitting},
    Author = {Aalst, W. M. P. van der and Rubin, V. and Verbeek, H. M. W. and Dongen, B. F. van and Kindler, E. and G\"{u}nther, C. W.},
    Journal = {Software and Systems Modeling (SoSyM)},
    Year = {2010},
    Number = {1},
    Pages = {87--111},
    Volume = {9},
    Abstract = {Abstract. Process mining includes the automated discovery of processes from event logs. Based on observed events (e.g., activities being executed or messages being exchanged) a process model is constructed. One of the essential problems in process mining is that one cannot assume to have seen all possible behavior. At best, one has seen a representative subset. Therefore, classical synthesis techniques are not suitable as they aim at finding a model that is able to exactly reproduce the log. Existing process mining techniques try to avoid such "overfitting" by generalizing the model to allow for more behavior. This generalization is often driven by the representation language and very crude assumptions about completeness. As a result, parts of the model are "overfitting" (allow only what has actually been observed) while other parts may be "underfitting" (allow for much more behavior without strong support for it). None of the existing techniques enables the user to control the balance between "overfitting" and "underfitting". To address this, we propose a two-step approach. First, using a configurable approach, a transition system is constructed. Then, using the \theory of regions", the model is synthesized. The approach has been implemented in the context of ProM and overcomes many of the limitations of traditional approaches.},
    Doi = {10.1007/s10270-008-0106-z},
    File = {Preprint of published paper:http\://www.win.tue.nl/~hverbeek/downloads/preprints/Aalst10.pdf:PDF;SoSyM:http\://www.sosym.org/:URL},
    Owner = {hverbeek},
    Timestamp = {2008.11.04},
    Url = {http://www.springerlink.com/content/u43v780550278h4l/fulltext.pdf}
    }
  • [PDF] H. M. W. Verbeek and W. M. P. van der Aalst, Configuring ibm websphere monitor for process mining, 2010.
    [Bibtex]
    @Unpublished{Verbeek10d,
    Title = {Configuring IBM WebSphere Monitor for Process Mining},
    Author = {Verbeek, H. M. W. and Aalst, W. M. P. van der},
    Year = {2010},
    Abstract = {Process mining has emerged as a way to discover or check the conformance of processes based on event logs. This enables organizations to learn from processes as they really take place. Since web services are distributed over autonomous parties, it is vital to monitor the correct execution of service processes. Fortunately, the \web services stack" assists in collecting structured event logs. These logs can be used to extract new information about service processes (like bottlenecks) and to check the conformance. In this paper, we demonstrate that such an event log can be obtained in the context of the IBMs WebSphere environment. More specifically, we show how to configure the WebSphere Business Monitor in such a way that it collects all the information needed for generating an event log.},
    File = {Pre-print of unpublished paper:http\://www.win.tue.nl/~hverbeek/downloads/preprints/Verbeek10d.pdf:URL},
    Owner = {hverbeek},
    Timestamp = {2012.09.20},
    Url = {http://www.win.tue.nl/~hverbeek/downloads/preprints/Verbeek10d.pdf}
    }
  • [PDF] H. M. W. Verbeek, J. C. A. M. Buijs, B. F. van Dongen, and W. M. P. van der Aalst, “Prom 6: the process mining toolkit,” in Proc. of bpm demonstration track 2010, Hoboken, USA, 2010, pp. 34-39.
    [Bibtex]
    @InProceedings{Verbeek10c,
    Title = {ProM 6: The Process Mining Toolkit},
    Author = {Verbeek, H. M. W. and Buijs, J. C. A. M. and Dongen, B. F. van and Aalst, W. M. P. van der},
    Booktitle = {Proc. of BPM Demonstration Track 2010},
    Year = {2010},
    Address = {Hoboken, USA},
    Editor = {La Rosa, M.},
    Month = {September},
    Pages = {34--39},
    Publisher = {CEUR-WS.org},
    Series = {CEUR Workshop Proceedings},
    Volume = {615},
    Abstract = {Process mining has been around for a decade, and it has proven to be a very fertile and successful research field. Part of this success can be contributed to the ProM tool, which combines most of the existing process mining techniques as plug-ins in a single tool. ProM 6 removes many limitations that existed in the previous versions, in particular with respect to the tight integration between the tool and the GUI.
    ProM 6 has been developed from scratch and uses a completely redesigned architecture. The changes were driven by many real-life applications and new insights into the design of process analysis software. Furthermore, the introduction of XESame in this toolkit allows for the conversion of logs to the ProM native format without programming.},
    File = {Preprint of published paper:http\://www.win.tue.nl/~hverbeek/downloads/preprints/Verbeek10c:URL},
    Owner = {hverbeek},
    Timestamp = {2010.07.22},
    Url = {http://ceur-ws.org/Vol-615/paper13.pdf}
    }
  • [PDF] H. M. W. Verbeek, J. C. A. M. Buijs, B. F. van Dongen, and W. M. P. van der Aalst, Xes tools, 2010.
    [Bibtex]
    @Misc{Verbeek10b,
    Title = {XES Tools},
    Author = {Verbeek, H. M. W. and Buijs, J. C. A. M. and Dongen, B. F. van and Aalst, W. M. P. van der},
    HowPublished = {CAiSE 2010 Forum},
    Month = {June},
    Year = {2010},
    Abstract = {Process mining has emerged as a new way to analyze business processes based on event logs. These events logs need to be extracted from operational systems and can subsequently be used to discover or check the conformance of processes. ProM is a widely used tool for process mining. In earlier versions of ProM, MXML was used as an input format. In future releases of ProM, a new logging format will be used: the eXtensible Event Stream (XES) format. This format has several advantages over MXML. The paper presents two tools that use this format - XESame and ProM6 - and highlights the main innovations and the role of XES. XESame enables domain experts to specify how the event log should be extracted from existing systems and converted to XES. ProM6 is a completely new process mining framework based on XES and enabling innovative process mining functionality.},
    File = {Preprint of published paper:http\://www.win.tue.nl/~hverbeek/downloads/preprints/Verbeek10b:URL},
    Owner = {hverbeek},
    Timestamp = {2010.06.25},
    Url = {http://www.processmining.org/_media/publications/verbeek2010.pdf}
    }
  • [PDF] [DOI] H. M. W. Verbeek and M. T. Wynn, “Verification,” in Modern business process automation: yawl and its support environment, A. H. M. ter Hofstede, W. M. P. van der Aalst, M. Adams, and N. Russell, Eds., Springer, Berlin, Germany, 2010, pp. 517-545.
    [Bibtex]
    @InCollection{Verbeek10a,
    Title = {Verification},
    Author = {Verbeek, H. M. W. and Wynn, M. T.},
    Booktitle = {Modern Business Process Automation: YAWL and its Support Environment},
    Publisher = {Springer, Berlin, Germany},
    Year = {2010},
    Chapter = {20},
    Editor = {Hofstede, A. H. M. ter and Aalst, W. M. P. van der and Adams, M. and Russell, N.},
    Pages = {517--545},
    Series = {Database Management \& Info Retrieval},
    Doi = {10.1007/978-3-642-03121-2 20},
    File = {Preprint of published paper:http\://www.win.tue.nl/~hverbeek/downloads/preprints/Verbeek10a:URL},
    Owner = {hverbeek},
    Timestamp = {2009.06.05}
    }
  • [PDF] [DOI] H. M. W. Verbeek, M. T. Wynn, W. M. P. van der Aalst, and A. H. M. ter Hofstede, “Reduction rules for reset/inhibitor nets,” Journal of computer and system sciences, vol. 76, iss. 2, pp. 125-143, 2010.
    [Bibtex]
    @Article{Verbeek10,
    Title = {Reduction Rules for Reset/Inhibitor Nets},
    Author = {Verbeek, H. M. W. and Wynn, M. T. and Aalst, W. M. P. van der and Hofstede, A. H. M. ter},
    Journal = {Journal of Computer and System Sciences},
    Year = {2010},
    Number = {2},
    Pages = {125--143},
    Volume = {76},
    Abstract = {Reset/inhibitor nets are Petri nets extended with reset arcs and inhibitor arcs. \wil{}{These extensions can be used to model cancelation and blocking. }A reset arc allows a transition to remove all tokens from a certain place when the transition fires. An inhibitor arc can stop a transition from being enabled if the place contains one or more tokens. While reset/inhibitor nets increase the expressive power of Petri nets, they also result in increased complexity of analysis techniques. One way of speeding up Petri net analysis is to apply reduction rules. Unfortunately, many of the rules defined for classical Petri nets do not hold in the presence of reset and/or inhibitor arcs. Moreover, new rules can be added. This is the first paper systematically presenting a comprehensive set of reduction rules for reset/inhibitor nets. These rules are liveness and boundedness preserving and are able to dramatically reduce models and their state spaces. \arthur{Note}{It can be observed} that most of the modeling languages used in practice have features related to cancelation and blocking. Therefore, this work is highly relevant for all kinds of application areas where analysis is currently intractable.},
    Doi = {10.1016/j.jcss.2009.06.003},
    File = {Preprint of published paper:http\://www.win.tue.nl/~hverbeek/downloads/preprints/Verbeek10.pdf:URL},
    Owner = {hverbeek},
    Timestamp = {2009.06.05}
    }

Leave a Reply