Institutions of the University of Bayreuth
Chair Business Administration XIX - Information Systems and Process Analytics

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Jump to: 2025 | 2024 | 2022 | 2021
Number of items at this level: 6.

2025

Volltext
Janssen, Dominik:
Datenbasierte Aktivitätserkennung mit Process Mining auf Sensordaten.
Bayreuth , 2025 . - IX, 178 p.
( Doctoral thesis, 2025 , Universität Bayreuth, Rechts- und Wirtschaftswissenschaftliche Fakultät)
DOI: https://doi.org/10.15495/EPub_UBT_00008700

Brzychczy, Edyta ; Aleknonytė-Resch, Milda ; Janssen, Dominik ; Koschmider, Agnes:
Process mining on sensor data : a review of related works.
In: Knowledge and Information Systems. Vol. 67 (2025) Issue 6 . - pp. 4915-4948.
DOI: https://doi.org/10.1007/s10115-024-02297-y

2024

Baum, Matthias ; Streeb, Mirjam ; Koschmider, Agnes:
Supercharging Obsessions with AI? The Development of Obsessive Passion Due to Reinforcing AI Feedback.
2024
Event: Rencontres de St-Gall: "The Mechanical Turk and its Grandchildren ante portas: The Significance of Artificial Intelligence in Entrepreneurship Research and Practice" , 02.-04.September 2024 , St. Gallen, Schweiz.
(Conference item: Conference , Speech )

2022

Zisgen, Yorck ; Janssen, Dominik ; Koschmider, Agnes:
Generating Synthetic Sensor Event Logs for Process Mining.
In: de Weerdt, Jochen ; Polyvyanyy, Artem (ed.): Intelligent Information Systems. - Cham, Schweiz : Springer Nature, 2022 . - pp. 130-137 . - (Lecture Notes in Business Information Processing ; 452 )
DOI: https://doi.org/10.1007/978-3-031-07481-3_15

Volltext
Renz, Matthias ; Koschmider, Agnes ; Kröger, Peer:
Vorwort zum Sonderheft „Cross-Domain Fusion“ - Heft 2.
In: Informatik Spektrum. Vol. 45 (2022) Issue 5 . - pp. 269-270.
DOI: https://doi.org/10.1007/s00287-022-01506-8

2021

Janssen, Dominik ; Mannhardt, Felix ; Koschmider, Agnes ; van Zelst, Sebastiaan J.:
Process Model Discovery from Sensor Event Data.
In: Leemans, Sander ; Leopold, Henrik (ed.): Process Mining Workshops. - Cham, Schweiz : Springer Nature, 2021 . - pp. 69-81 . - (Lecture Notes in Business Information Processing ; 406 )
DOI: https://doi.org/10.1007/978-3-030-72693-5_6

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