Process Mining Workshops ICPM 2022 International Workshops, Bozen-Bolzano, Italy, October 23–28, 2022, Revised Selected Papers /

Process Mining Workshops ICPM 2022 International Workshops, Bozen-Bolzano, Italy, October 23–28, 2022, Revised Selected Papers / [electronic resource] : edited by Marco Montali, Arik Senderovich, Matthias Weidlich. - 1st ed. 2023. - XI, 592 p. 282 illus., 140 illus. in color. online resource. - Lecture Notes in Business Information Processing, 468 1865-1356 ; . - Lecture Notes in Business Information Processing, 468 .

Open Access

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).

9783031278150

10.1007/978-3-031-27815-0 doi


Data mining.
Information technology--Management.
Machine learning.
Medical informatics.
Data Mining and Knowledge Discovery.
Business Process Management.
Machine Learning.
Computer Application in Administrative Data Processing.
Health Informatics.

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