Logo des Repositoriums
 

Describing Behavior Sequences of Fattening Pigs Using Process Mining

Kurzanzeige
dc.contributor.authorLepsien, Arvid
dc.contributor.authorMelfsen, Andreas
dc.contributor.authorBosselmann, Jan
dc.contributor.authorKoschmider, Agnes
dc.contributor.authorHartung, Eberhard
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.abstractProcess mining is a well-established technique for gaining insights into event data. It allows significant insights into event data in terms of identifying process anomalies, giving hints between as-is and to-be process states or making predictions based on data. Although process mining has been successfully applied in many application domains like healthcare, finance, and manufacturing, additional domains might also benefit from process mining like life and natural sciences. However, these domains mainly do not rely on structured business data that is expected as input for process mining algorithms. Rather, data from these domains first has to be efficiently pre-processed. This paper suggests process mining as an approach to identify behavioral patterns of fattening pigs from video data. The goal of this approach is to demonstrate that process mining might be a valuable tool for understanding the behavior of pigs by considering and analyzing their behavior sequences. Furthermore, additional insights can be gained in terms of temporal and spatial analysis about the division of the pig pen in functional areas. In this way, new implications might be found about pig behavior compared to existing state-of-the art approaches in the field.en
dc.identifier.doi10.18420/EMISA2024_07
dc.identifier.isbn978-3-88579-743-2
dc.identifier.issn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44019
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofEMISA 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-349
dc.subjectProcess Mining
dc.subjectUnstructured Data
dc.subjectBehavior Sequences
dc.subjectFattening Pigs
dc.titleDescribing Behavior Sequences of Fattening Pigs Using Process Miningen
mci.conference.date13–14 March 2024
mci.conference.locationPotsdam
mci.conference.sessiontitleEnterprise Modeling and Information Systems Architecture (EMISA 2024)
mci.reference.pages41-42

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
C1-5.pdf
Größe:
137.38 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P349 - EMISA 2024 Enterprise Modelling and Information Systems Architectures