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This open access book constitutes revised selected papers from the
International Workshops held at the Third International Conference
on Process Mining, ICPM 2021, which took place in Eindhoven, The
Netherlands, during October 31-November 4, 2021. 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
28 papers included in this volume were carefully reviewed and
selected from 65 submissions. They stem from the following
workshops: 2nd International Workshop on Event Data and Behavioral
Analytics (EDBA) 2nd International Workshop on Leveraging Machine
Learning in Process Mining (ML4PM) 2nd International Workshop on
Streaming Analytics for Process Mining (SA4PM) 6th International
Workshop on Process Querying, Manipulation, and Intelligence (PQMI)
4th International Workshop on Process-Oriented Data Science for
Healthcare (PODS4H) 2nd International Workshop on Trust, Privacy,
and Security in Process Analytics (TPSA) One survey paper on the
results of the XES 2.0 Workshop is included.
Process mining techniques can be used to discover, analyze and
improve real processes, by extracting models from observed
behavior. The aim of this book is conformance checking, one of the
main areas of process mining. In conformance checking, existing
process models are compared with actual observations of the process
in order to assess their quality. Conformance checking techniques
are a way to visualize the differences between assumed process
represented in the model and the real process in the event log,
pinpointing possible problems to address, and the business process
management results that rely on these models. This book combines
both application and research perspectives. It provides concrete
use cases that illustrate the problems addressed by the techniques
in the book, but at the same time, it contains complete
conceptualization and formalization of the problem and the
techniques, and through evaluations on the quality and the
performance of the proposed techniques. Hence, this book brings the
opportunity for business analysts willing to improve their
organization processes, and also data scientists interested on the
topic of process-oriented data science.
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