6 papers
AVOCADO: The Streaming Process Mining Challenge
Christian Imenkamp, Andrea Maldonado, Hendrik Reiter +4
Streaming process mining deals with the real-time analysis of streaming data. Event streams require algorithms capable of processing data incrementally. To systematically address t…
ContinuumConductor : Decentralized Process Mining on the Edge-Cloud Continuum
Hendrik Reiter, Janick Edinger, Martin Kabierski +10
Process mining traditionally assumes centralized event data collection and analysis. However, modern Industrial Internet of Things systems increasingly operate over distributed, re…
Determining Window Sizes using Species Estimation for Accurate Process Mining over Streams
Christian Imenkamp, Martin Kabierski, Hendrik Reiter +3
Streaming process mining deals with the real-time analysis of event streams. A common approach for it is to adopt windowing mechanisms that select event data from a stream for subs…
Process Mining on Distributed Data Sources
Maximilian Weisenseel, Julia Andersen, Samira Akili +10
Major domains such as logistics, healthcare, and smart cities increasingly rely on sensor technologies and distributed infrastructures to monitor complex processes in real time. Th…
EdgeMiner: Distributed Process Mining at the Data Sources
Julia Andersen, Patrick Rathje, Christian Imenkamp +2
Process mining is moving beyond mining traditional event logs and nowadays includes, for example, data sourced from sensors in the Internet of Things (IoT). The volume and velocity…
Ranking the Top-K Realizations of Stochastically Known Event Logs
Arvid Lepsien, Marco Pegoraro, Frederik Fonger +3
Various kinds of uncertainty can occur in event logs, e.g., due to flawed recording, data quality issues, or the use of probabilistic models for activity recognition. Stochasticall…