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Assisted Data Annotation for Business Process Information Extraction from Textual Documents

Title data

Neuberger, Julian ; van der Aa, Han ; Ackermann, Lars ; Buschek, Daniel ; Herrmann, Jannic ; Jablonski, Stefan:
Assisted Data Annotation for Business Process Information Extraction from Textual Documents.
In: Comuzzi, Marco ; Grigori, Daniela ; Sellami, Mohamed ; Zhou, Zhangbing (ed.): Cooperative Information Systems. - Cham : Springer Nature Switzerland , 2025 . - pp. 186-203
ISBN 978-3-031-81375-7
DOI: https://doi.org/10.1007/978-3-031-81375-7_11

Abstract in another language

Machine-learning based generation of process models from natural language text process descriptions provides a solution for the time-intensive and expensive process discovery phase. Many organizations have to carry out this phase, before they can utilize business process management and its benefits. Yet, research towards this is severely restrained by an apparent lack of large and high-quality datasets. This lack of data can be attributed to, among other things, an absence of proper tool assistance for business process information extraction dataset creation, resulting in high workloads and inferior data quality. We explore two assistance features to support dataset creation, a recommendation system for identifying process information in the text and visualization of the current state of already identified process information as a graphical business process model. A controlled user study with 31 participants shows that assisting dataset creators with recommendations lowers all aspects of workload, up to -51.0%, and significantly improves annotation quality, up to +38.9% in F₁ score. We make all data and code available to encourage further research on additional novel assistance strategies.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Business process management; Process information extraction; Natural language processing; Human computer interaction
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: 15 May 2025 05:51
Last Modified: 15 May 2025 05:51
URI: https://eref.uni-bayreuth.de/id/eprint/93567