1 citations · 2 across the 6 of their papers we have counts for
6 papers
AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation
Lukas Kirchdorfer, Robert Blümel, Timotheus Kampik +2
Business process simulation (BPS) is a versatile technique for estimating process performance across various scenarios. Traditionally, BPS approaches employ a control-flow-first pe…
A Universal Prompting Strategy for Extracting Process Model Information from Natural Language Text using Large Language Models
Julian Neuberger, Lars Ackermann, Han van der Aa +1
Over the past decade, extensive research efforts have been dedicated to the extraction of information from textual process descriptions. Despite the remarkable progress witnessed i…
Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining Tasks
Adrian Rebmann, Fabian David Schmidt, Goran Glavaš +1
The process mining community has recently recognized the potential of large language models (LLMs) for tackling various process mining tasks. Initial studies report the capability…
PGTNet: A Process Graph Transformer Network for Remaining Time Prediction of Business Process Instances
Keyvan Amiri Elyasi, Han van der Aa, Heiner Stuckenschmidt
We present PGTNet, an approach that transforms event logs into graph datasets and leverages graph-oriented data for training Process Graph Transformer Networks to predict the remai…
From OCEL to DOCEL -- Datasets and Automated Transformation
Alexandre Goossens, Adrian Rebmann, Johannes De Smedt +2
Object-centric event data represent processes from the point of view of all the involved object types. This perspective has gained interest in recent years as it supports the analy…
GECCO: Constraint-driven Abstraction of Low-level Event Logs
Adrian Rebmann, Matthias Weidlich, Han van der Aa
Process mining enables the analysis of complex systems using event data recorded during the execution of processes. Specifically, models of these processes can be discovered from e…