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Improving process models by mining mappings of low-level events to high-level activities

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Abstract

While it is possible to analyze the run-time behavior of a business process through process mining techniques, in practice there is often a gap between the low-level nature of the events recorded in an event log and the high-level of abstraction at which the process is modeled. This makes it difficult to understand the recorded behavior in terms of the high-level activities in the process model. Also, it makes it difficult to improve the model based on run-time data about the process. In this work we present an approach to mine mappings between the events in the log and the activities in the model. These mappings can be used to generate suggestions of how the process model can be extended in order to capture the behavior recorded in the event log. Using a real-world and publicly available event log, we show how the approach can improve the model in a stepwise manner, until it covers all the behavior recorded in the event log.

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Notes

  1. For simplicity, in the text we often refer to a micro-sequence as a “sequence of events”, even though what we actually mean is the “sequence of symbols” (μ), to be fully precise.

  2. http://www.win.tue.nl/bpi/2013/challenge

  3. The event log has the following DOI reference: 10.4121/uuid:500573e6-accc-4b0c-9576-aa5468b10cee

References

  • de Leoni, M., & van der Aalst, W.M.P. (2013a). Aligning event logs and process models for multi-perspective conformance checking: an approach based on integer linear programming. In Business process management of LNCS (Vol. 8094, pp. 113–129). Springer.

  • de Leoni, M., & van der Aalst, W.M.P. (2013b). Data-aware process mining: discovering decisions in processes using alignments. In Proceedings of the 28th annual ACM symposium on applied computing (pp. 1454–1461). ACM.

  • de Leoni, M., Maria Maggi, F., Van der Aalst, W.M.P. (2012a). Aligning event logs and declarative process models for conformance checking. In Business process management of LNCS (Vol. 7481, pp. 82–97). Springer.

  • de Leoni, M., Van der Aalst, W.M.P., Van Dongen, B.F. (2012b). Data- and resource-aware conformance checking of business processes. In Business information systems of LNBIP (Vol. 117, pp. 48–59). Springer.

  • de Medeiros, A.K.A., & Weijters, A.J.M.M. (2005). Genetic process mining. In Applications and theory of petri nets 2005 of LNCS (Vol. 3536, pp. 48–69). Springer.

  • de Medeiros, A.K.A., Weijters, A.J.M.M., van der Aalst, W.M.P. (2007). Genetic process mining: an experimental evaluation. Data Mining and Knowledge Discovery, 14(2), 245–304.

    Article  MathSciNet  Google Scholar 

  • Ferreira, D.R., Szimanski, F., Ralha, C.G. (2013a). A hierarchical Markov model to understand the behaviour of agents in business processes. In Business process management workshops of LNBIP (Vol. 132, pp. 150–161). Springer.

  • Ferreira, D.R., Szimanski, F., Ralha, C.G. (2013b). Mining the low-level behavior of agents in high-level business processes. International Journal of Business Process Integration and Management, 6(2), 146–166.

    Article  Google Scholar 

  • Greco, G., Guzzo, A., Pontieri, L. (2005). Mining hierarchies of models: from abstract views to concrete specifications. In 3rd international conference on business process management of LNCS (Vol. 3649, pp. 32–47). Springer.

  • Günther, C.W., Rozinat, A., van der Aalst, W.M.P. (2010). Activity mining by global trace segmentation. In BPM 2009 international workshops of LNBIP (Vol. 43, pp. 128–139). Springer.

  • Günther, C.W., & Van der Aalst, W.M.P. (2007). Fuzzy mining – adaptive process simplification based on multi-perspective metrics. In 5th international conference on business process management of LNCS (Vol. 4714, pp. 328–343). Springer.

  • Hornung, T., Koschmider, A., Lausen, G. (2008). Recommendation based process modeling support: method and user experience. In Conceptual modeling - ER 2008 of LNCS (Vol. 5321, pp. 265–278). Springer., Springer.

  • Jagadeesh Chandra Bose, R.P., Verbeek, E.H.M.W., van der Aalst, M.P. (2012). Discovering hierarchical process models using ProM. In CAiSE Forum 2011 of LNBIP (Vol. 107, pp. 33–48). Springer.

  • Koschmider, A., Hornung, T., Oberweis, A. (2011). Recommendation-based editor for business process modeling. Data & Knowledge Engineering, 70(6), 483–503.

    Article  Google Scholar 

  • Koschmider, A., Song, M., Reijers, H.A. (2009). Advanced social features in a recommendation system for process modeling. In Business information systems of LNBIP (Vol. 21, pp. 109–120). Springer.

  • Mans, R.S., Schonenberg, M.H., Song, M., Aalst, W.M.P., Bakker, P.J.M. (2009). Application of process mining in healthcare – a case study in a dutch hospital In A. Fred, J. Filipe, H. Gamboa (Eds.), Biomedical Engineering Systems and Technologies of CCIS (Vol. 25, pp. 425–438): Springer.

  • OMG (2011). Business Process Model and Notation (BPMN), Version 2.0.

  • Rozinat, A., & van der Aalst, W.M.P. (2008). Conformance checking of processes based on monitoring real behavior. Information Systems, 33(1), 64–95.

    Article  Google Scholar 

  • Scheer, A.-W. (2000). ARIS: Business Process Modeling, 3rd edn. Springer.

  • Schonenberg, H., Weber, B., van Dongen, B., van der Aalst, W. (2008). Supporting flexible processes through recommendations based on history. In Business process management, (Vol. 5240 of LNCS, pp. 51–66). Springer.

  • Szimanski, F., Ralha, C.G., Wagner, G., Ferreira, D.R. (2013). Improving business process models with agent-based simulation and process mining. In Enterprise, business-process and information systems modeling, (Vol. 147 of LNBIP, pp. 124–138). Springer.

  • van Bon, J., & Pieper, M. (2005). Foundations of IT Service Management: based on ITIL. Van Haren Publishing van der Veen, A., & Verheijen, T. (Eds.)

  • van der Aalst, W.M.P. (2011). Process mining: discovery, conformance and enhancement of business processes. Springer.

  • van der Aalst, W.M.P., & Weijters, A.J.M.M. (2004). Process mining: a research agenda. Computers in Industry, 53(3), 231–244.

    Article  Google Scholar 

  • van der Aalst, W.M.P., Weijters, A.J.M.M., Maruster, L. (2004). Workflow mining: discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering, 16, 1128–1142.

    Article  Google Scholar 

  • van der Aalst, W.M.P. (2012). Process mining. Communications of the ACM, 55(8), 76–83.

    Article  Google Scholar 

  • van der Aalst, W.M.P. (1998). The application of Petri nets to workflow management. The Journal of Circuits, Systems and Computers, 8(1), 21–66.

    Article  Google Scholar 

  • van der Aalst, W.M.P., Adriansyah, A., van Dongen, B. (2012). Replaying history on process models for conformance checking and performance analysis. WIREs Data Mining and Knowledge Discovery, 2(2), 182–192.

    Article  Google Scholar 

  • Vanderfeesten, I., Reijers, H.A., van der Aalst, W.M.P. (2008). Product based workflow support: A recommendation service for dynamic workflow execution. BPM Center Report BPM-08-03, BPMcenter.org.

  • Weijters, A.J.M.M., van der Aalst, W.M.P., de Medeiros, A.A.K. (2006). Process mining with the HeuristicsMiner algorithm. Technical Report WP 166. Eindhoven University of Technology.

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Authors and Affiliations

  1. Universidade de Lisboa, Instituto Superior Técnico (IST), Lisbon, Portugal

    Diogo R. Ferreira

  2. Departamento de Ciência da Computação, Universidade de Brasília (UnB), Brasília, Brazil

    Fernando Szimanski & Célia G. Ralha

Authors
  1. Diogo R. Ferreira
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  2. Fernando Szimanski
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  3. Célia G. Ralha
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Correspondence to Diogo R. Ferreira.

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Ferreira, D.R., Szimanski, F. & Ralha, C.G. Improving process models by mining mappings of low-level events to high-level activities. J Intell Inf Syst 43, 379–407 (2014). https://doi.org/10.1007/s10844-014-0327-2

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  • DOI: https://doi.org/10.1007/s10844-014-0327-2

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