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Authors: M. Amin Yazdi 1 ; Pejman Farhadi Ghalatia 2 and Benedikt Heinrichs 1

Affiliations: 1 IT Center, RWTH Aachen University, Aachen, Germany ; 2 Aachen Institute for Advanced Study in Computational Engineering Science, RWTH Aachen University, Aachen, Germany

Keyword(s): Business Process Intelligence, Event Log Abstraction, Process Discovery, Data Pre-processing.

Abstract: Process mining provides various techniques in response to the increasing demand for understanding the execution of the underlying processes of software systems. The discovery and conformance checking techniques allow for the analysis of event data and verify compliances. However, in real-life scenarios, the event data recorded by software systems often contain numerous activities resulting in unstructured process models that are not usable by domain experts. Hence, event log abstraction is an essential preprocessing step to deliver a desired abstracted model that is human-readable and enables process analysis. This paper provides an overview of the literature and proposes a novel approach for transforming fine-granular event logs generated from client-server applications to a higher level of abstraction suitable for domain experts for further analysis. Moreover, we demonstrate the validity of the suggested method with the help of two case studies.

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Paper citation in several formats:
Yazdi, M.; Farhadi Ghalatia, P. and Heinrichs, B. (2021). Event Log Abstraction in Client-Server Applications. In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR; ISBN 978-989-758-533-3; ISSN 2184-3228, SciTePress, pages 27-36. DOI: 10.5220/0010652000003064

@conference{kdir21,
author={M. Amin Yazdi. and Pejman {Farhadi Ghalatia}. and Benedikt Heinrichs.},
title={Event Log Abstraction in Client-Server Applications},
booktitle={Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR},
year={2021},
pages={27-36},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010652000003064},
isbn={978-989-758-533-3},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR
TI - Event Log Abstraction in Client-Server Applications
SN - 978-989-758-533-3
IS - 2184-3228
AU - Yazdi, M.
AU - Farhadi Ghalatia, P.
AU - Heinrichs, B.
PY - 2021
SP - 27
EP - 36
DO - 10.5220/0010652000003064
PB - SciTePress

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