bei Google ScholarTitelangaben
Neuberger, Julian ; Doll, Leonie ; Engelmann, Benedikt ; Ackermann, Lars ; Jablonski, Stefan:
Leveraging Data Augmentation for Process Information Extraction.
In: van der Aa, Han ; Bork, Dominik ; Schmidt, Rainer ; Sturm, Arnon
(Hrsg.):
Enterprise, Business-Process and Information Systems Modeling : Proceedings. -
Cham, Switzerland
: Springer Nature
,
2024
. - S. 57-70
. - (Lecture Notes in Business Information Processing
; 511
)
ISBN 978-3-031-61007-3
DOI: https://doi.org/10.1007/978-3-031-61007-3_6
Abstract
Business Process Modeling projects often require formal process models as a central component. High costs associated with the creation of such formal process models motivated many different fields of research aimed at automated generation of process models from readily available data. These include process mining on event logs and generating business process models from natural language texts. Research in the latter field is regularly faced with the problem of limited data availability, hindering both evaluation and development of new techniques, especially learning-based ones.
Weitere Angaben
| Publikationsform: | Aufsatz in einem Buch |
|---|---|
| Begutachteter Beitrag: | Ja |
| Institutionen der Universität: | Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Angewandte Informatik IV > Lehrstuhl Angewandte Informatik IV - Univ.-Prof. Dr.-Ing. Stefan Jablonski |
| Titel an der UBT entstanden: | Ja |
| Themengebiete aus DDC: | 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik |
| Eingestellt am: | 30 Okt 2024 11:32 |
| Letzte Änderung: | 30 Okt 2024 11:32 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/90904 |