145 citations · 334 across the 11 of their papers we have counts for
14 papers
The Interplay Between High-Level Problems and The Process Instances That Give Rise To Them
Bianka Bakullari, Jules van Thoor, Dirk Fahland +1
Business processes may face a variety of problems due to the number of tasks that need to be handled within short time periods, resources' workload and working patterns, as well as…
Chit-Chat or Deep Talk: Prompt Engineering for Process Mining
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…
Extracting and Pre-Processing Event Logs
Dirk Fahland
Event data is the basis for all process mining analysis. Most process mining techniques assume their input to be an event log. However, event data is rarely recorded in an event lo…
AI-Augmented Business Process Management Systems: A Research Manifesto
Marlon Dumas, Fabiana Fournier, Lior Limonad +11
AI-Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the…
Striking a new balance in accuracy and simplicity with the Probabilistic Inductive Miner
Dennis Brons, Roeland Scheepens, Dirk Fahland
Numerous process discovery techniques exist for generating process models that describe recorded executions of business processes. The models are meant to generalize executions int…
Process Discovery Using Graph Neural Networks
Dominique Sommers, Vlado Menkovski, Dirk Fahland
Automatically discovering a process model from an event log is the prime problem in process mining. This task is so far approached as an unsupervised learning problem through graph…
Inferring Unobserved Events in Systems With Shared Resources and Queues
Dirk Fahland, Vadim Denisov, Wil. M. P. van der Aalst
To identify the causes of performance problems or to predict process behavior, it is essential to have correct and complete event data. This is particularly important for distribut…
Multi-Dimensional Event Data in Graph Databases
Stefan Esser, Dirk Fahland
Process event data is usually stored either in a sequential process event log or in a relational database. While the sequential, single-dimensional nature of event logs aids queryi…
Scalable Alignment of Process Models and Event Logs: An Approach Based on Automata and S-Components
Daniel Reißner, Abel Armas-Cervantes, Raffaele Conforti +3
Given a model of the expected behavior of a business process and an event log recording its observed behavior, the problem of business process conformance checking is that of ident…
The Imprecisions of Precision Measures in Process Mining
Niek Tax, Xixi Lu, Natalia Sidorova +2
In process mining, precision measures are used to quantify how much a process model overapproximates the behavior seen in an event log. Although several measures have been proposed…
Modeling Styles in Business Process Modeling
Jakob Pinggera, Pnina Soffer, Stefan Zugal +5
Research on quality issues of business process models has recently begun to explore the process of creating process models. As a consequence, the question arises whether different…
Tying Process Model Quality to the Modeling Process: The Impact of Structuring, Movement, and Speed
Jan Claes, Irene Vanderfeesten, Hajo A. Reijers +7
In an investigation into the process of process modeling, we examined how modeling behavior relates to the quality of the process model that emerges from that. Specifically, we con…
Artifact Lifecycle Discovery
Viara Popova, Dirk Fahland, Marlon Dumas
Artifact-centric modeling is a promising approach for modeling business processes based on the so-called business artifacts - key entities driving the company's operations and whos…
Maximal Structuring of Acyclic Process Models
Artem Polyvyanyy, Luciano García-Bañuelos, Dirk Fahland +1
This paper contributes to the solution of the problem of transforming a process model with an arbitrary topology into an equivalent structured process model. In particular, this pa…