no code implementations • 23 Jan 2024 • Dirk Fahland, Fabian Fournier, Lior Limonad, Inna Skarbovsky, Ava J. E. Swevels
The functionality of these services is to elicit the various knowledge ingredients that underlie SAX explanations.
no code implementations • 19 Jul 2023 • Urszula Jessen, Michal Sroka, Dirk Fahland
This research investigates the application of Large Language Models (LLMs) to augment conversational agents in process mining, aiming to tackle its inherent complexity and diverse skill requirements.
no code implementations • 30 Jan 2022 • Marlon Dumas, Fabiana Fournier, Lior Limonad, Andrea Marrella, Marco Montali, Jana-Rebecca Rehse, Rafael Accorsi, Diego Calvanese, Giuseppe De Giacomo, Dirk Fahland, Avigdor Gal, Marcello La Rosa, Hagen Völzer, Ingo Weber
AI-Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology.
1 code implementation • 13 Sep 2021 • Dominique Sommers, Vlado Menkovski, Dirk Fahland
In this paper, we explore the problem of supervised learning of a process discovery technique D. We introduce a technique for training an ML-based model D using graph convolutional neural networks; D translates a given input event log into a sound Petri net.
no code implementations • 27 Feb 2021 • Dirk Fahland, Vadim Denisov, Wil. M. P. van der Aalst
To understand and analyze the behavior and performance of processes with shared resources, we aim to reconstruct bounds for timestamps of events in a case that must have happened but were not recorded by inference over events in other cases in the system.
no code implementations • 22 Oct 2019 • Daniel Reißner, Abel Armas-Cervantes, Raffaele Conforti, Marlon Dumas, Dirk Fahland, Marcello La Rosa
To address this limitation, the paper proposes a second technique wherein the process model is first decomposed into a set of automata, known as S-components, such that the product of these automata is equal to the automaton of the whole process model.
Software Engineering
no code implementations • 3 May 2017 • Niek Tax, Xixi Lu, Natalia Sidorova, Dirk Fahland, Wil M. P. van der Aalst
In process mining, precision measures are used to quantify how much a process model overapproximates the behavior seen in an event log.