activity
20132026
most citedPredictive Monitoring of Business Processes

286 citations · 848 across the 35 of their papers we have counts for

collaborators

42 papers

cs.AI2026

Supporting Autonomous Process Execution within a Multi-Perspective Constraint Frame via Numeric Planning

Paul Wittlinger, Giacomo Acitelli, Anti Alman +2

AI-Augmented Business Process Management Systems (ABPMS) enhance traditional BPMS by leveraging advanced AI techniques to define, execute, and monitor complex process structures. W…

cs.AI2026

On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discovery

Anti Alman, Izack Cohen, Avigdor Gal +2

A core component of any AI-Augmented Business Process Management System (ABPMS) is the process frame, which gives the system process-awareness and defines its maximal behavioral bo…

cs.SE2025

Executing Discrete/Continuous Declarative Process Specifications via Complex Event Processing

Leo Poss, Stefan Schönig, Fabrizio Maria Maggi

Traditional Business Process Management (BPM) focuses on discrete events and fails to incorporate critical continuous sensor data in cyber-physical environments. Hybrid declarative…

cs.AI2024

Conformance Checking of Fuzzy Logs against Declarative Temporal Specifications

Ivan Donadello, Paolo Felli, Craig Innes +2

Traditional conformance checking tasks assume that event data provide a faithful and complete representation of the actual process executions. This assumption has been recently que…

cs.AI2024★ 6 cited

Guiding the generation of counterfactual explanations through temporal background knowledge for Predictive Process Monitoring

Andrei Buliga, Chiara Di Francescomarino, Chiara Ghidini +2

Counterfactual explanations suggest what should be different in the input instance to change the outcome of an AI system. When dealing with counterfactual explanations in the field…

cs.AI2023★ 2 cited

Knowledge-Driven Modulation of Neural Networks with Attention Mechanism for Next Activity Prediction

Ivan Donadello, Jonghyeon Ko, Fabrizio Maria Maggi +3

Predictive Process Monitoring (PPM) aims at leveraging historic process execution data to predict how ongoing executions will continue up to their completion. In recent years, PPM…