Logo des Repositoriums
 

Addressing the Log Representativeness Problem using Species Discovery (Extended Abstract)

dc.contributor.authorKabierski, Martin
dc.contributor.authorRichter, Markus
dc.contributor.authorWeidlich, Matthias
dc.contributor.editorLaue, Ralf
dc.contributor.editorFahrenkrog-Petersen, Stephan
dc.date.accessioned2024-05-08T08:24:46Z
dc.date.available2024-05-08T08:24:46Z
dc.date.issued2024
dc.description.abstractEvent logs are generated during the enactment of process-centric information systems and form the basis for optimization, monitoring, and enhancement initiatives of said systems. As such, they enable a data-driven and unbiased evaluation of the as-is state of the underlying processes. Yet, since at any time, event logs represent merely a sample of the whole possible behaviour of the information system, insights are only actionable should the event log be representative of the information system from which it is derived. Therefore, the question arises of how the representativeness of an event log$L with respect to its generative system P can be quantified, given that only L is present. In this work, we argue, that representativeness of an event log needs to be assessed with an intended analysis question in mind and discuss log completeness as one important facet of representativeness. We show how established estimators from biodiversity research can be utilized to quantify log completeness.en
dc.identifier.doi10.18420/EMISA2024_08
dc.identifier.isbn978-3-88579-743-2
dc.identifier.issn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44020
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofEMISA 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-349
dc.subjectEvent Logs
dc.subjectCompleteness
dc.titleAddressing the Log Representativeness Problem using Species Discovery (Extended Abstract)en
mci.conference.date13–14 March 2024
mci.conference.locationPotsdam
mci.conference.sessiontitleEnterprise Modeling and Information Systems Architecture (EMISA 2024)
mci.reference.pages43-44

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
C1-6.pdf
Größe:
153.7 KB
Format:
Adobe Portable Document Format