Privacy-Preserving Process Mining with PM4Py (Extended Abstract) (bibtex)

by Henrik Kirchmann, Stephan A. Fahrenkrog-Petersen, Martin Kabierski, Han van der Aa, and Matthias Weidlich

Reference:

Privacy-Preserving Process Mining with PM4Py (Extended Abstract) (Henrik Kirchmann, Stephan A. Fahrenkrog-Petersen, Martin Kabierski, Han van der Aa, and Matthias Weidlich), In Proceedings of the ICPM Doctoral Consortium and Demo Track 2022 co-located with 4th International Conference on Process Mining (ICPM 2022), Bolzano, Italy, October, 2022 (Marwan Hassani, Agnes Koschmider, Marco Comuzzi, Fabrizio Maria Maggi, Luise Pufahl, eds.), CEUR-WS.org, volume 3299, 2022.

Bibtex Entry:

@inproceedings{DBLP:conf/icpm/KirchmannFKAW22,
  author    = {Henrik Kirchmann and
               Stephan A. Fahrenkrog{-}Petersen and
               Martin Kabierski and
               Han van der Aa and
               Matthias Weidlich},
  editor    = {Marwan Hassani and
               Agnes Koschmider and
               Marco Comuzzi and
               Fabrizio Maria Maggi and
               Luise Pufahl},
  title     = {Privacy-Preserving Process Mining with PM4Py (Extended Abstract)},
  booktitle = {Proceedings of the {ICPM} Doctoral Consortium and Demo Track 2022
               co-located with 4th International Conference on Process Mining {(ICPM}
               2022), Bolzano, Italy, October, 2022},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {3299},
  pages     = {85--89},
  publisher = {CEUR-WS.org},
  year      = {2022},
  url       = {https://ceur-ws.org/Vol-3299/Paper18.pdf},
  timestamp = {Fri, 10 Mar 2023 16:22:44 +0100},
  biburl    = {https://dblp.org/rec/conf/icpm/KirchmannFKAW22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}