Alexander Seeliger

Learning of Process Representations Using Recurrent Neural Networks

In process mining, many tasks use a simplified representation of a single case to perform tasks like trace clustering, anomaly detection, or subset identification. These representations may capture the control flow of the process as well as the context a case is executed in. However, most of these representations are hand-crafted, which is very time-consuming […]

02: Process discovery Main Track
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