Probabilistic and Non-Deterministic Event Data in Process Mining: Embedding Uncertainty in Process Analysis Techniques

Process mining is a subfield of process science that analyzes event data collected in databases called event logs. Recently, novel types of event data have become of interest due to the wide industrial application of process mining analyses. In this paper, we examine uncertain event data. Such data...

Full description

Saved in:
Bibliographic Details
Published inarXiv.org
Main Author Pegoraro, Marco
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 11.05.2022
Subjects
Industrial applications
Uncertainty
Online AccessGet full text

Cover

More Information
Summary:Process mining is a subfield of process science that analyzes event data collected in databases called event logs. Recently, novel types of event data have become of interest due to the wide industrial application of process mining analyses. In this paper, we examine uncertain event data. Such data contain meta-attributes describing the amount of imprecision tied with attributes recorded in an event log. We provide examples of uncertain event data, present the state of the art in regard of uncertainty in process mining, and illustrate open challenges related to this research direction.
ISSN:2331-8422