This article needs additional citations for verification. (July 2023) |
The IEEE Task Force on Process Mining (TFPM) is a non-commercial association for process mining. The IEEE (Institute of Electrical and Electronics Engineers) Task Force on Process Mining was established in October 2009 as part of the IEEE Computational Intelligence Society at the Eindhoven University of Technology.[1][2][3][4][5]
Founded | 2006 |
---|---|
Founder | Eindhoven University of Technology |
Key people |
|
Website | https://www.tf-pm.org/ |
The task force is supported by over 80 organizations and has around 750 members.[6] The main goal of the task force is to promote the research, development, education, and understanding of process mining.[7]
About
editIn 2012, the IEEE World Congress on Computational Intelligence/ IEEE Congress on Evolutionary Computation held a session on Process Mining.[8] Process mining is a type of research that is a mix of computational intelligence and data mining, as well as process modeling and analysis.[8]
Activities and organization
editThe Task Force on Process Mining has a Steering Committee[9] and an Advisory Board.[10] The Steering Committee, was chaired by Wil van der Aalst in its inception in 2009, defined 15 action lines. These include the organization of the annual International Process Mining Conference (ICPM) series,[11] standardization efforts leading to the IEEE XES standard for storing and exchanging event data[12][13], and the Process Mining Manifesto[14][15] which was translated into 16 languages. The Task Force on Process Mining also publishes a newsletter, provides data sets, organizes workshops and competitions, and connects researchers and practitioners.
In 2016, the IEEE Standards Association published the IEEE Standard for Extensible Event Stream (XES), which is a widely accepted file format by the process mining community.[16]
As of 2023, Boudewijn van Dongen serves as chair of the Steering Committee. Wil van der Aalst and Moe Wynn both serve as vice-chair of the Steering Committee. [17]
See also
editReferences
edit- ^ "IEEE Task Force on Process Mining". Home page of the task force on process mining. IEEE Task Force on Process Mining. Retrieved 10 January 2021.
- ^ "Process mining". IONOS Digital Guide. Retrieved 2022-09-08.
- ^ Innovates, Dallas; Murray, Lance (2022-09-05). "Mindzie Taps Member of IEEE Task Force on Process Mining As Strategic Adviser". Dallas Innovates. Retrieved 2023-06-30.
- ^ "start | IEEE CIS Task Force on Process Mining". www.win.tue.nl. Retrieved 2023-08-25.
- ^ "What is task mining? | IBM". www.ibm.com. Retrieved 2023-09-27.
- ^ "Supporting organizations - IEEE Task Force on Process Mining". www.tf-pm.org. Retrieved 2021-01-10.
- ^ van der Aalst, Wil (2016). Process Mining: Data Science in Action.
- ^ a b "TFPM 2012 - IEEE Task Force on Process Mining". conference.researchbib.com. Retrieved 2023-08-25.
- ^ "Steering Committee - IEEE Task Force on Process Mining". www.tf-pm.org. Retrieved 2021-01-10.
- ^ "Advisory Board - IEEE Task Force on Process Mining". www.tf-pm.org. Retrieved 2021-01-10.
- ^ "International Process Mining Conference (ICPM) series". Home page of the ICPM conference series. IEEE Task Force on Process Mining. Retrieved 10 January 2021.
- ^ IEEE Standard for eXtensible Event Stream (XES) for Achieving Interoperability in Event Logs and Event Streams. ieee. 11 November 2016. doi:10.1109/IEEESTD.2016.7740858. ISBN 978-1-5044-2421-9. Retrieved 10 January 2021.
{{cite book}}
:|website=
ignored (help) - ^ "eXtensible Event Stream (XES)". eXtensible Event Stream (XES). IEEE Task Force on Process Mining. 11 November 2016. Retrieved 10 January 2021.
- ^ "Process Mining Manifesto". Process Mining Manifesto. IEEE Task Force on Process Mining. 2011. Retrieved 10 January 2021.
- ^ "Process Mining Manifesto" (PDF).
- ^ Kingsley, Okoye (2020-04-10). Applications and Developments in Semantic Process Mining. IGI Global. ISBN 978-1-7998-2670-5.
- ^ "Steering Committee - IEEE Task Force on Process Mining". www.tf-pm.org. Retrieved 2023-10-19.
Further reading
edit- Aalst, W. van der (2016). Process Mining: Data Science in Action. Springer Verlag, Berlin (ISBN 978-3-662-49850-7).
- Reinkemeyer, L. (2020). Process Mining in Action: Principles, Use Cases and Outlook. Springer Verlag, Berlin (ISBN 978-3-030-40171-9).