Deducing Case IDs for Unlabeled Event Logs

dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorBayomie, Dina
dc.contributor.authorMA Helal, Iman
dc.contributor.authorAwad, Ahmed
dc.contributor.authorEzat, Ehab
dc.contributor.authorElBastawissi, Ali
dc.date.accessioned2020-01-29T07:24:44Z
dc.date.available2020-01-29T07:24:44Z
dc.date.issued2016
dc.descriptionMSA Google Scholaren_US
dc.description.abstractEvent logs are invaluable sources of knowledge about the actual execution of processes. A large number of techniques to mine, check conformance and analyze performance have been developed based on logs. All these techniques require at least case ID, activity ID and the timestamp to be in the log. If one of those is missing, these techniques cannot be applied. Real life logs are rarely originating from a centrally orchestrated process execution. Thus, case ID might be missing, known as unlabeled log. This requires a manual preprocessing of the log to assign case ID to events in the log. In this paper, we propose a new approach to deduce case ID for the unlabeled event log depending on the knowledge about the process model. We provide a set of labeled logs instead of a single labeled log with different rankings. We evaluate our prototypical implementation against similar approaches.en_US
dc.description.sponsorshipSpringeren_US
dc.description.urihttps://www.scimagojr.com/journalsearch.php?q=145291&tip=sid&clean=0
dc.identifier.isbn978-3-319-42886-4
dc.identifier.urihttps://t.ly/WV69
dc.language.isoenen_US
dc.publisherSpringer, Chamen_US
dc.relation.ispartofseriesInternational Conference on Business Process Management;
dc.subjectOctober University for University for Unlabeled event logen_US
dc.subjectMissing dataen_US
dc.subjectEvent correlationen_US
dc.subjectDecision treesen_US
dc.subjectProcess miningen_US
dc.subjectUnmanaged business processen_US
dc.titleDeducing Case IDs for Unlabeled Event Logsen_US
dc.typeBook chapteren_US

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