at Google ScholarTitle data
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
(ed.):
Enterprise, Business-Process and Information Systems Modeling : Proceedings. -
Cham, Switzerland
: Springer Nature
,
2024
. - pp. 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 in another language
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.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | Yes |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV > Chair Applied Computer Science IV - Univ.-Prof. Dr.-Ing. Stefan Jablonski |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
| Date Deposited: | 30 Oct 2024 11:32 |
| Last Modified: | 30 Oct 2024 11:32 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/90904 |