Preserving Complex Object-Centric Graph Structures to Improve Machine Learning Tasks in Process Mining

Interactions of multiple processes and different objects can be captured using object-centric event data. Object-centric event data represent process executions as event graphs of interacting objects. When applying machine learning techniques to …

A Generic Approach to Extract Object-Centric Event Data from Databases Supporting SAP ERP

Optimizing Resource Allocation Based on Predictive Process Monitoring

Performance-preserving event log sampling for predictive monitoring

ocpa: A Python library for object-centric process analysis

Action-Oriented Process Mining: Bridging the Gap Between Insights and Actions

Discovery of Resource-Oriented Transition Systems for Yield Enhancement in Semiconductor Manufacturing

In semiconductor manufacturing, data-driven methodologies have enabled the resolution of various issues, particularly yield management and enhancement. Yield, one of the crucial key performance indicators in semiconductor manufacturing, is mostly …

Quality-Aware Resource Model Discovery

Context-aware process mining aims at extending a contemporary approach with process contexts for realistic process modeling. Regarding this discipline, there have been several attempts to combine process discovery and predictive process modeling and …

A Scalable Database for the Storage of Object-Centric Event Logs

Predicting performances in business processes using deep neural networks

Online operational support is gaining increasing interest due to the availability of real-time data and sufficient computing power, such as predictive business process monitoring. Predictive business process monitoring aims at providing timely …