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Process Mining Manifesto

  • Conference paper
  • Open Access

Part of the Lecture Notes in Business Information Processing book series (LNBIP,volume 99)

Abstract

Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.

Keywords

  • Process Mining
  • Business Process Management
  • Business Intelligence
  • Concept Drift
  • Process Instance

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Berlin (2011)

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© 2012 Springer-Verlag Berlin Heidelberg

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van der Aalst, W. et al. (2012). Process Mining Manifesto. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds) Business Process Management Workshops. BPM 2011. Lecture Notes in Business Information Processing, vol 99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28108-2_19

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  • DOI: https://doi.org/10.1007/978-3-642-28108-2_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28107-5

  • Online ISBN: 978-3-642-28108-2

  • eBook Packages: Computer ScienceComputer Science (R0)