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Daniel Schuster
Daniel Schuster
Fraunhofer Institute for Applied Information Technology FIT
Bestätigte E-Mail-Adresse bei fit.fraunhofer.de
Titel
Zitiert von
Zitiert von
Jahr
Utilizing domain knowledge in data-driven process discovery: A literature review
D Schuster, SJ van Zelst, WMP van der Aalst
Computers in Industry 137, 2022
352022
A framework for extracting and encoding features from object-centric event data
JN Adams, G Park, S Levich, D Schuster, WMP van der Aalst
Service-Oriented Computing. ICSOC 2022, 36-53, 2022
242022
Incremental Discovery of Hierarchical Process Models
D Schuster, SJ van Zelst, WMP van der Aalst
Research Challenges in Information Science. RCIS 2020, 417-433, 2020
242020
Cortado—An interactive tool for data-driven process discovery and modeling
D Schuster, SJ Zelst, WMP van der Aalst
Application and Theory of Petri Nets and Concurrency. PETRI NETS 2021, 465-475, 2021
212021
Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm
D Schuster, SJ van Zelst
Business Process Management. BPM 2020, 147-164, 2020
182020
Defining cases and variants for object-centric event data
JN Adams, D Schuster, S Schmitz, G Schuh, WMP van der Aalst
2022 4th International Conference on Process Mining (ICPM), 128-135, 2022
172022
Cortado: A dedicated process mining tool for interactive process discovery
D Schuster, SJ van Zelst, WMP van der Aalst
SoftwareX 22, 101373, 2023
102023
PM4Py: A process mining library for Python
A Berti, S van Zelst, D Schuster
Software Impacts 17, 100556, 2023
92023
Alignment Approximation for Process Trees
D Schuster, S van Zelst, WMP van der Aalst
Process Mining Workshops. ICPM 2020, 247-259, 2021
92021
Freezing sub-models during incremental process discovery
D Schuster, SJ van Zelst, WMP van der Aalst
Conceptual Modeling. ER 2021, 14-24, 2021
82021
Scalable online conformance checking using incremental prefix-alignment computation
D Schuster, GJ Kolhof
Service-Oriented Computing – ICSOC 2020 Workshops., 379-394, 2020
82020
Visualizing Trace Variants from Partially Ordered Event Data
D Schuster, L Schade, SJ van Zelst, WMP van der Aalst
Process Mining Workshops. ICPM 2021, 34-46, 2021
72021
Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case Study
A Berti, D Schuster, WMP van der Aalst
Business Process Management Workshops. BPM 2023, 427-439, 2024
62024
The process mining toolkit (pmtk): Enabling advanced process mining in an integrated fashion
A Berti, CY Li, D Schuster, SJ van Zelst
ICPM 2021 Doctoral Consortium and Demo Track 2021, 43-44, 2021
62021
Conformance Checking for Trace Fragments Using Infix and Postfix Alignments
D Schuster, N Föcking, SJ van Zelst, WMP van der Aalst
Cooperative Information Systems. CoopIS 2022, 299-310, 2022
52022
Supporting Users in the Continuous Evolution of Automated Routines in Their Smart Spaces
E Serral, D Schuster, Y Bertrand
Business Process Management Workshops. BPM 2021, 391-402, 2021
42021
Control-Flow-Based Querying of Process Executions from Partially Ordered Event Data
D Schuster, M Martini, SJ van Zelst, WMP van der Aalst
Service-Oriented Computing. ICSOC 2022, 19-35, 2022
32022
Temporal Performance Analysis for Block-Structured Process Models in Cortado
D Schuster, L Schade, SJ van Zelst, WMP van der Aalst
Intelligent Information Systems. CAiSE 2022., 110-119, 2022
32022
Scalable Discovery of Partially Ordered Workflow Models with Formal Guarantees
H Kourani, D Schuster, W Van Der Aalst
2023 5th International Conference on Process Mining (ICPM), 89-96, 2023
22023
Mining Frequent Infix Patterns from Concurrency-Aware Process Execution Variants
M Martini, D Schuster, WMP van der Aalst
Proceedings of the VLDB Endowment 16 (10), 2666-2678, 2023
22023
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