• Media type: E-Book
  • Title: Process Mining Workshops : ICPM 2022 International Workshops, Bozen-Bolzano, Italy, October 23–28, 2022, Revised Selected Papers
  • Contributor: Montali, Marco [HerausgeberIn]; Senderovich, Arik [HerausgeberIn]; Weidlich, Matthias [HerausgeberIn]
  • imprint: Cham: Springer Nature Switzerland, 2023.
    Cham: Imprint: Springer, 2023.
  • Published in: Lecture Notes in Business Information Processing ; 468
  • Issue: 1st ed. 2023.
  • Extent: 1 Online-Ressource(XI, 592 p. 188 illus., 140 illus. in color.)
  • Language: English
  • DOI: 10.1007/978-3-031-27815-0
  • ISBN: 9783031278150
  • Identifier:
  • Keywords: Information technology—Management. ; Data mining. ; Machine learning. ; Medical informatics. ; Information technology
  • Origination:
  • Footnote: Open Access
  • Description: This open access book constitutes revised selected papers from the International Workshops held at the 4th International Conference on Process Mining, ICPM 2022, which took place in Bozen-Bolzano, Italy, during October 23–28, 2022. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 42 papers included in this volume were carefully reviewed and selected from 89 submissions. They stem from the following workshops: – 3rd International Workshop on Event Data and Behavioral Analytics (EDBA) – 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) – 3rd International Workshop on Responsible Process Mining (RPM) (previously known as Trust, Privacy and Security Aspects in Process Analytics) – 5th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) – 3rd International Workshop on Streaming Analytics for Process Mining (SA4PM) – 7th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) – 1st International Workshop on Education meets Process Mining (EduPM) – 1st International Workshop on Data Quality and Transformation in Process Mining (DQT-PM).
  • Access State: Open Access