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ORCIDDaniel Schuster 0001
Person information
- affiliation: Fraunhofer FIT, Sankt Augustin, Germany
- affiliation: RWTH Aachen University, Germany
Other persons with the same name
- Daniel Schuster — disambiguation page
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2020 – today
- 2024
[j6]Daniel Schuster
, Francesca Zerbato, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Defining and visualizing process execution variants from partially ordered event data. Inf. Sci. 657: 119958 (2024)- [c20]Alessandro Berti, Humam Kourani, Hannes Häfke, Chiao-Yun Li, Daniel Schuster:
Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, and Evaluation Strategies. BPMDS/EMMSAD@CAiSE 2024: 13-21 - [c19]Humam Kourani, Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
Process Modeling with Large Language Models. BPMDS/EMMSAD@CAiSE 2024: 229-244 - [i14]Humam Kourani, Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
ProMoAI: Process Modeling with Generative AI. CoRR abs/2403.04327 (2024) - [i13]Alessandro Berti, Humam Kourani, Hannes Häfke, Chiao-Yun Li, Daniel Schuster:
Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, Evaluation Strategies, and Future Challenges. CoRR abs/2403.06749 (2024) - [i12]Humam Kourani, Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
Process Modeling With Large Language Models. CoRR abs/2403.07541 (2024) - 2023
- [j5]Gyunam Park, Daniel Schuster, Wil M. P. van der Aalst:
Pattern-based action engine: Generating process management actions using temporal patterns of process-centric problems. Comput. Ind. 153: 104020 (2023) - [j4]Michael Martini, Daniel Schuster, Wil M. P. van der Aalst:
Mining Frequent Infix Patterns from Concurrency-Aware Process Execution Variants. Proc. VLDB Endow. 16(10): 2666-2678 (2023) - [j3]Alessandro Berti, Sebastiaan J. van Zelst, Daniel Schuster:
PM4Py: A process mining library for Python. Softw. Impacts 17: 100556 (2023) - [j2]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Cortado: A dedicated process mining tool for interactive process discovery. SoftwareX 22: 101373 (2023) - [c18]Daniel Schuster, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Incremental Discovery of Process Models Using Trace Fragments. BPM 2023: 55-73 - [c17]Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case Study. Business Process Management Workshops 2023: 427-439 - [c16]Humam Kourani, Daniel Schuster, Wil M. P. van der Aalst:
Scalable Discovery of Partially Ordered Workflow Models with Formal Guarantees. ICPM 2023: 89-96 - [i11]Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst:
Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case Study. CoRR abs/2307.02194 (2023) - 2022
- [j1]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Utilizing domain knowledge in data-driven process discovery: A literature review. Comput. Ind. 137: 103612 (2022) - [c15]Daniel Schuster, Lukas Schade, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Temporal Performance Analysis for Block-Structured Process Models in Cortado. CAiSE Forum 2022: 110-119 - [c14]Daniel Schuster, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Conformance Checking for Trace Fragments Using Infix and Postfix Alignments. CoopIS 2022: 299-310 - [c13]Giorgi Lomidze, Daniel Schuster, Chiao-Yun Li, Sebastiaan J. van Zelst:
Enhanced Transformation of BPMN Models with Cancellation Features. EDOC 2022: 128-144 - [c12]Jan Niklas Adams, Daniel Schuster, Seth Schmitz, Günther Schuh, Wil M. P. van der Aalst:
Defining Cases and Variants for Object-Centric Event Data. ICPM 2022: 128-135 - [c11]Daniel Schuster, Michael Martini, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Control-Flow-Based Querying of Process Executions from Partially Ordered Event Data. ICSOC 2022: 19-35 - [c10]Jan Niklas Adams, Gyunam Park, Sergej Levich, Daniel Schuster, Wil M. P. van der Aalst:
A Framework for Extracting and Encoding Features from Object-Centric Event Data. ICSOC 2022: 36-53 - [c9]Daniel Schuster, Emanuel Domnitsch, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
A Generic Trace Ordering Framework for Incremental Process Discovery. IDA 2022: 264-277 - [i10]Jan Niklas Adams, Daniel Schuster, Seth Schmitz, Günther Schuh, Wil M. P. van der Aalst:
Defining Cases and Variants for Object-Centric Event Data. CoRR abs/2208.03235 (2022) - [i9]Jan Niklas Adams, Gyunam Park, Sergej Levich, Daniel Schuster, Wil M. P. van der Aalst:
A Framework for Extracting and Encoding Features from Object-Centric Event Data. CoRR abs/2209.01219 (2022) - [i8]Daniel Schuster, Niklas Föcking, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Conformance Checking for Trace Fragments Using Infix and Postfix Alignments. CoRR abs/2209.04290 (2022) - [i7]Daniel Schuster, Michael Martini, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Control-Flow-Based Querying of Process Executions from Partially Ordered Event Data. CoRR abs/2211.04146 (2022) - 2021
- [c8]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Cortado - An Interactive Tool for Data-Driven Process Discovery and Modeling. Petri Nets 2021: 465-475 - [c7]Estefanía Serral, Daniel Schuster, Yannis Bertrand:
Supporting Users in the Continuous Evolution of Automated Routines in Their Smart Spaces. Business Process Management Workshops 2021: 391-402 - [c6]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Freezing Sub-models During Incremental Process Discovery. ER 2021: 14-24 - [c5]Daniel Schuster, Lukas Schade, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Visualizing Trace Variants from Partially Ordered Event Data. ICPM Workshops 2021: 34-46 - [i6]Daniel Schuster, Gero J. Kolhof:
Scalable Online Conformance Checking Using Incremental Prefix-Alignment Computation. CoRR abs/2101.00958 (2021) - [i5]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Cortado - An Interactive Tool for Data-Driven Process Discovery and Modeling. CoRR abs/2105.07666 (2021) - [i4]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Freezing Sub-Models During Incremental Process Discovery: Extended Version. CoRR abs/2108.00215 (2021) - [i3]Daniel Schuster, Lukas Schade, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Visualizing Trace Variants From Partially Ordered Event Data. CoRR abs/2110.02060 (2021) - 2020
- [c4]Daniel Schuster, Sebastiaan J. van Zelst:
Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm. BPM 2020: 147-164 - [c3]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Alignment Approximation for Process Trees. ICPM Workshops 2020: 247-259 - [c2]Daniel Schuster, Gero Joss Kolhof:
Scalable Online Conformance Checking Using Incremental Prefix-Alignment Computation. ICSOC Workshops 2020: 379-394 - [c1]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Incremental Discovery of Hierarchical Process Models. RCIS 2020: 417-433 - [i2]Daniel Schuster, Sebastiaan J. van Zelst:
Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm. CoRR abs/2002.05945 (2020) - [i1]Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst:
Alignment Approximation for Process Trees. CoRR abs/2009.14094 (2020)
Coauthor Index
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last updated on 2024-06-20 00:16 CEST by the dblp team
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