MA Helal, ImanAwad, AhmedElBastawissi, Ali2020-01-302020-01-302015978-1-5090-0479-9https://doi.org/10.1109/AICCSA.2015.7507132https://cutt.ly/yrYp5HiMSA Google ScholarEvents produced from business process execution need identification of process instance. With the lack of a central execution, it is hard to correlate these events to specific cases. Monitoring business processes is useful in conformance checking, compliance enforcement, risk management, and performance analysis. However, all these techniques and approaches need a set of correlated events. We present an approach to fill the gap in real life situations, between execution of unmanaged events and the stack of techniques and approaches that need labeled events at runtime to generate further analysis. This approach works on the unlabeled events, either online (as a stream of events) or offline (as a batch file of events). It deduces the case identifier for each unlabeled event, and displays the results of possible case identifiers with their rankings. Also the generated events can be filed in different event logs with different rankings to be further analyzed by other techniques and approachesenOctober University for University for Unlabeled EventUnmanaged business processEvent StreamsProcess MonitoringDecision treesBook chapterhttps://doi.org/10.1109/AICCSA.2015.7507132