9 papers
Inductive Process Discovery from Partially Ordered Event Data
Humam Kourani, Tom Breuer, Gyunam Park +1
The Inductive Miner (IM) family is a prominent class of process discovery techniques, combining efficient recursive decomposition with soundness-by-construction guarantees. However…
Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text
Anton Antonov, Humam Kourani, Alessandro Berti +1
Process modeling is a sub-domain of Business Process Management (BPM) focused on the translation of process artifacts into formal models. This task traditionally requires extensive…
Neuro-Symbolic Process Anomaly Detection
Devashish Gaikwad, Wil M. P. van der Aalst, Gyunam Park
Process anomaly detection is an important application of process mining for identifying deviations from the normal behavior of a process. Neural network-based methods have recently…
Compliance-Aware Predictive Process Monitoring: A Neuro-Symbolic Approach
Fabrizio De Santis, Gyunam Park, Wil M. P. van der Aalst +1
Existing approaches for predictive process monitoring are sub-symbolic, meaning that they learn correlations between descriptive features and a target feature fully based on data,…
Neuro-Symbolic Learning for Predictive Process Monitoring via Two-Stage Logic Tensor Networks with Rule Pruning
Fabrizio De Santis, Gyunam Park, Francesco Zanichelli
Predictive modeling on sequential event data is critical for fraud detection and healthcare monitoring. Existing data-driven approaches learn correlations from historical data but…
PMAx: An Agentic Framework for AI-Driven Process Mining
Anton Antonov, Humam Kourani, Alessandro Berti +2
Process mining provides powerful insights into organizational workflows, but extracting these insights typically requires expertise in specialized query languages and data science…
Online Discovery of Simulation Models for Evolving Business Processes (Extended Version)
Francesco Vinci, Gyunam Park, Wil van der Aalst +1
Business Process Simulation (BPS) refers to techniques designed to replicate the dynamic behavior of a business process. Many approaches have been proposed to automatically discove…
Synchronizing Process Model and Event Abstraction for Grounded Process Intelligence (Extended Version)
Janik-Vasily Benzin, Gyunam Park, Stefanie Rinderle-Ma
Model abstraction (MA) and event abstraction (EA) are means to reduce complexity of (discovered) models and event data. Imagine a process intelligence project that aims to analyze…
INEXA: Interactive and Explainable Process Model Abstraction Through Object-Centric Process Mining
Janik-Vasily Benzin, Gyunam Park, Juergen Mangler +1
Process events are recorded by multiple information systems at different granularity levels. Based on the resulting event logs, process models are discovered at different granulari…